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UBC Theses and Dissertations

Land-use and water quality : a GIS evaluation of the problems, interaction, and initiatives, in the Pampanga… Mapili, Mariano Cadanilla 1996

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L A N D - U S E A N D W A T E R QUALITY: A G I S E V A L U A T I O N OF THE PROBLEMS, INTERACTION, A N D INITIATIVES, I N THE P A M P A N G A R l V E R B A S I N , C E N T R A L L U Z O N , PHILIPPINES BY M A R I A N O C A D A N I L L A MAPIL I , JR. B.Sc, University of the Philippines at Los Banos, 1982 M . S c , University of the Philippines at Los Banos, 1990 A THESIS SUBMITTED IN PARTIAL FULF ILLMENT OF THE REQUIREMENTS FOR THE D E G R E E OF D O C T O R OF PHILOSOPHY IN T H E F A C U L T Y OF G R A D U A T E STUDIES (RESOURCE M A N A G E M E N T A N D E N V I R O N M E N T A L STUDIES) We accept this thesis as conforming to the required standard The University of British Columbia May, 1996 (D 1996 Mariano Cadanillla Mapili, Jr. In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of fk sOUtc UmxPOf^ WrJ- f r f t l ^ f e n W t W S M « J The University of British Columbia Vancouver, Canada Date X\ J q n x [ffifr DE-6 (2/88) 11 ABSTRACT Agricultural activities in the Pampanga river Basin (PRB) are threatened by the increasing population and development thrusts of the Philippine government. This study was conducted to develop a framework by which problems, initiatives, and interactions among land-use changes, water quality and governance issues may be assessed employing Geographic Information Systems (GIS) techniques. Stream stations were sampled for nitrate, phosphate, temperature, dissolved oxygen, total dissolved solids, chemical oxygen demand and pH. Land-use changes were analyzed through GIS, while land-use planning was investigated through workshop participation and review of government plans. Agricultural land increased 0.6% annually from 1953 to 1980 due to conversion of grasslands, wetlands and forests to agriculture, and declined 0.5 % annually from 1980 to 1993 due to expansion of settlements. A provincial land-use plan would accelerate conversion rather than protect agricultural lands. Water quality in the Pampanga river and its tributaries is deteriorating in both the spatial and temporal dimensions. The eruption of Mt. Pinatubo was responsible for increased levels of ortho-phosphate, TDS, and temperature in streams, but the low DO during the start of the rainy season and the high nitrate-N concentrations are indicators of human influence on water quality. Streams with catchments having the same predominant land-use classification exhibited similar trends in water quality. Animal species in different area classifications also affected water quality at different flow periods. Buffer analysis on 500 metre zone along the streams gave best values. The effect of runoff is altered by the type of land-use, specifically the presence of rice fields. Ill The management of nitrate-N based on a nitrogen budget revealed that animal manure and inorganic fertilizer are major sources of nitrogen in the basin. The hotspot areas are catchments with large settlement areas, and/or with a very high animal population. Alternative scenarios revealed no significant changes in water quality even with a three-fold increase in animal production or 10 % agricultural land conversion. A cautious optimism is anticipated in involving the barangay captains in the overall management of the environment, in particular, the control of stream pollution that endangers the fishing industry. iv T A B L E OF CONTENTS Page Abstract ii Table of Contents iv List of Tables viii List of Figures ix List of Abbreviations xiii Acknowledgment xv 1. INTRODUCTION 1.1 The issue: Changing land-use and water quality-emerging threats to sustainable agriculture 1 1.2 Research Goal 4 1.3 Specific Objectives 4 1.4 The case study site: Pampanga River Basin 5 1.4.1 The physical environment of the Central Plains 5 1.4.2 Climate 6 1.4.3 Soils and agricultural economy 10 1.4.4 Human Population 11 1.4.5 The Upper Pampanga River Project (UPRP) 13 1.4.6 Study site boundary 14 1.5 Review of previous work 15 1.6 A contribution to the understanding of land-use-water quality interaction in the Philippines 17 2. M E T H O D S 2.1 Field method 19 2.1.1 Parameters measured 19 2.1.2 Water quality sampling stations (WQSS) 21 2.1.3 Sampling frequency and strategy 22 2.2 Surveys, interviews and reports 24 2.2.1 Department of Environment and Natural Resources 25 2.2.2 Planning offices 25 2.2.3 Barangay Captains 26 2.3 GIS and statistical analysis 27 3. A SSESSMENT OF T H E LAND-USE CHANGES IN T H E P A M P A N G A R I V E R BASIN : T H E CASE OF T H E EXPANDING AND SHRINKING RICE GRANARY 3.1 Land-use changes in the basin 31 3.1.1 The expansion years: 1953 to 1980 35 3.1.2 The vanishing years: 1980 to 1993 36 3.1.3 Summary of land-use changes from 1953 to 1993 38 3.2 Food land base and settlements conflict: The Nueva Ecija Area Case Study 40 3.3 Unsustainable changes in the land 46 4. L A N D - U S E P L A N N I N G A N D M A N A G E M E N T I N T H E P A M P A N G A R I V E R B A S I N : P R O B L E M S A N D I N I T I A T I V E S 4.1 The approach to land-use planning in the N E D A ' s Development Plans 48 4.1.1 N E D A ' s development plans 49 4.1.2 Problems and opportunities in regional land-use planning 55 4.2 The Nueva Ecija Land-use plan and policy: A case study on land-use planning 58 4.2.1 Legal background of the project 59 4.2.2 The process 60 4.2.3 Problems associated with the process 61 4.3 The Nueva Ecija land-use plan: implications on the future of sustainable agriculture in the basin 64 4.3.1 A report and critique of the plan 65 4.3.2 Potential problems in implementation 69 4.4 Toward a land-use plan that supports agricultural sustainability 71 5. W A T E R Q U A L I T Y A S S E S S M E N T O F T H E P A M P A N G A R I V E R A N D I T S T R I B U T A R I E S 5.1 Discharge data for the Pampanga river system and die three periods 74 5.3 Water quality in the Pampanga river and tributaries 77 5.3.1 Temperature and dissolved oxygen 77 5.3.2 The buffering capacity of the system the case of p H and alkalinity 83 5.3.3 Total Dissolved Solids (TDS) and Chemical Oxygen Demand (COD) 89 5.3.4 Nutrients fNitrate-N and o-phosphate) and the risk of eutrophication 96 5.4 The water quality of the Pampanga River System in perspective 103 6. L A N D - U S E A N D W A T E R Q U A L I T Y I N T E R A C T I O N S 6.1 Cumulative contributing areas and buffer regions 106 6.2 Land-use and water quality interactions: land-use cover as index of non-point source pollution 107 6.2.1 Relationship between rice field and water quality 107 6.2.2 Relationship between settlements and water quality 110 6.2.3 Relationship between woodland and water quality I l l 6.2.4 Relationship between grassland and water quality 114 6.2.5 Relationship between wetlands and water quality 117 6.2.6 Relationship between lahar-covered areas and water quality 117 vi 6.3 Land-use activities and water quality interactions: the case of animal farms 120 6.3.1 Effect of animal farms on water quality 121 6.3.2 The animal unit equivalent (AUE) and water quality 127 6.3.3 Waste management in hog farms 129 6.4 Land-use activities and water quality interactions The case of human population 132 6.5 Land-use and water quality interactions: General Relationships 135 7. I M P L I C A T I O N S O F L A N D - U S E M A N A G E M E N T O N W A T E R Q U A L I T Y : T H E C A S E O F N I T R A T E - N I T R O G E N 7.1 The nitrogen budget 137 7.1.1 Sources of nitrogen 139 7.1.2 Sinks of nitrogen 144 7.1.3 Environmental nitrogen 145 7.2 Nitrogen management in the basin 147 7.2.1 The present condition 147 7.2.2 Scenario 1: Increasing animal production 151 7.2.3 Scenario 2: Decreasing areas under rice cultivation 152 7.3 Improving nitrogen management in the basin 155 8. T H E R O L E O F L O C A L G O V E R N M E N T (BARANGAY) O N T H E F U T U R E O F L A N D - U S E A N D W A T E R Q U A L I T Y I N T H E B A S I N 8.1 Background information on the respondents 8.1.1 Personal data 158 8.1.2 Personal knowledge of the evaluated stream 160 8.2 Perceptions on environmental problems 8.2.1 General environmental problems ; 162 8.2.2 Perceptions on stream pollution 164 8.3 Barangay Captain's competence for pollution control 8.3.1 Evidence for enforcement 168 8.3.2 The Local Government Code (LGC) and the Barangay Captains 172 8.4 A cautious optimism for pollution control through the Barangay Captain 175 9. S U M M A R Y , C O N C L U S I O N S , A N D R E C O M M E N D A T I O N S 9.1 Land-use changes and land-use planning 176 9.2 Water quality 178 9.3 Interaction between land-use and water quality 178 9.4 A framework for nitrogen management 179 9.5 Future for land-use and water quality: Perceptions of Barangay Captains 180 9.6 Recommendations 9.6.1 Improve land-use planning 181 9.6.2 Develop a new monitoring network 181 9.6.3 Enforce animal waste management operation 182 vii B I B L I O G R A P H Y 184 A P P E N D I C E S Appendix Table 2- la. Water Quality Data: Pampanga river and its tributaries (1993 to 1994) 193 Appendix 2-2a. Personal Communication 212 Appendix 2-3a. Water quality data from DPWH (1986 to-1993) 214 Appendix 2-4a. Sample cover letter and questionnaire used in the study 223 Appendix Table 6-la: Cumulative contributing areas of the stations 229 Appendix Table 7-la: Nitrogen fluxes of the different catchments 230 viii L I S T O F T A B L E S Table Page 2-2 Range and resolutions for the different parameters measured 21 2-3 Summary of data from government agencies used in the study 26 2- 4 Summary of maps used in creating the GIS base map 28 3- 1 Summary of land-use changes in the 1953 map boundary 39 3-2 Percentage of settlement area in three different buffer classifications and years 40 3- 3 Summary of land-use changes in the NuevaEcija Area 46 4- 1 Comparison of land-use in the Nueva Ecija Area when the plan is carried out 67 5- 1 Comparison of water quality parameters from study results with two polluted river systems in the Philippines 104 6- 1 Animal unit equivalents (AUE) used in the study 128 6-2 Efficiency of wastewater treatment facilities of animal farms on three water quality parameters 132 6- 3 Regression equations between nitrate-N and land-use cover and activities 136 7- 1 Computed 10 days evapo-transpiration data for Pampanga (LREP, 1986) 139 7-2 Conversion factors used in estimating nitrogen input for animals 139 7-3 Wet season fertilizer application in five different years in the basin, in percentage of farmers 141 7-4 Dry season fertilizer application in five different years in the basin, in percentage of farmers 142 7-5 Soil texture and assigned leaching rates 146 7-6 Run-off coefficients attributed to different slopes 147 7-7 Cumulative nitrogen fluxes in the Pampanga River Basin as determined at Station 57 148 7- 8 Factors affecting expected total nitrogen value 151 8- 1 Frequency distribution of age and residence of respondents 158 8-2 Occupation and educational attainment of respondents 159 8-3 Respondents' self-evaluation on environmental concern 159 8-4 Respondent familiarity with and awareness to the evaluated stream 160 8-5 Respondent familiarity with barangay boundary 161 8-6 Distance of respondents from streams 161 8-7 Respondents' ranking of five major problems 162 8-8 Repondents' ranking of environmental problems in their own barangays 163 8-9 Attractiveness of streams . . . 164 8-10 Potential and actual uses of the streams 164 8-11 Perception of stream pollution by respondents 165 8-12 Noticeable signs of pollution as perceived by respondents versus usual forms of complaints from constituents 165 8-13 Willingness to relocate residence 166 8-14 Evaluation of four probable causes of stream pollution by respondents 167 8-15 Community actions regarding pollution as perceived by respondents 168 8-16 Previous actions on pollution problems 169 8-17 Frequency of pollution complaints reported by constituents 169 8-18 Reaction of respondents to pollution problems 170 8-19 Respondents' information channels for the Local Government Code 173 ix L I S T O F F I G U R E S Figure page 1-1 Location map of the Pampanga River Basin 7 1-2 Elevation slice map of the basin 8 1- 3 The Pampanga river and its tributaries 9 2- 1 Frequency of sampling for each station 23 2- 2 The buffer zones along the major streams in Catchment No. 4 30 3- 1 Land-use evaluation of the Pampanga River Basin from 1:50,000 US Army topographic maps of 1953 32 3-2 Land-use evaluation of the Pampanga River Basin from 1:50,000 N A M R I A 1990 topographic Maps 33 3-3 Land-use evaluation of the Pampanga River Basin from 1:50i000 Nueva Ecija, Pampanga, Bulacan and Tarlac CENROs 34 3-4 Land-use dynamics from 1953 to 1980 36 3-5 Land-use dynamics from 1980 to 1993 37 3-6 The Nueva Ecija Area in relation to the whole Pampanga River Basin 41 3-7 Land-use evaluation of the Nueva Ecija Area from 1:50,000 Nueva Ecija CENROs (1993) 42 3-8 Land-use evaluation of the Nueva Ecija Area from 1:50,000 B S W M Land-use Maps (1988). 43 3- 9 Land-use dynamics from 1988 to 1993 in the Nueva Ecija Area 44 4- 1 Land-use evaluation of the Nueva Ecija Area from 1:50,000 Proposed Land-use Map (IDP/NE, 1994) 66 4- 2 Resulting land-use dynamics from 1993 if the proposed Nueva Ecija land-use plan is carried out 67 5- 1 Location of sampling stations and catchment boundaries 73 5-2 Divisions of the sampling period of the study in terms of the hydrographs of six sampling stations along the Pampanga River 75 5-3 Variability of discharge measurements of the Pampanga river and its tributaries 76 5-4 Fluctuations of mean discharge measurements along the Pampanga river 76 5-5 Variability in temperature of the Pampanga river and its tributaries 78 5-6 Fluctuations in mean temperature along the Pampanga river 78 5-7 Variability in dissolved oxygen concentration of the Pampanga river system 81 5-8 Dissolved oxygen concentration and % saturation in the Pampanga river system 81 5-9 Variability in pH of the Pampanga River system 84 X Figure page 5-10 Fluctuations in mean pH along the Pampanga river 84 5-11 Comparison of pH in selected stations along the Pampanga river and its tributaries from four sources in four different periods 86 5-12 Variability in pH of the Pampanga River and its tributaries from DPWH data 87 5-13 Variability in total alkalinity of the Pampanga River and its tributaries from DPWH data 88 5-14 Variability in total hardness on the Pampanga river and its tributaries from DPWH data 89 5-15 Variability in TDS of the Pampanga river and its tributaries 90 5-16 Fluctuations in mean TDS concentration along the Pampanga river 90 5-17 Variability in TDS of the Pampanga river and its tributaries from DPWH data 92 5-18 Comparison of TDS in selected stations along the Pampanga river and its tributaries from four sources in four different periods 93 5-19 Variability in COD of the Pampanga river and its tributaries 95 5-20 Fluctuations in mean COD concentration along the Pampanga river 95 5-21 Variability in nitrate-N of the Pampanga river and its tributaries 97 5-22 Fluctuations in mean nitrate-N concentration along the Pampanga river 97 5-23 Variability in ortho-phosphate concentration of the Pampanga river and its tributaries 100 5-24 Fluctuations in mean ortho-phosphate concentration along the Pampanga river . . 100 5-25 N:P ratio of mainstem stations in three different flow periods 102 5- 26 N:P ratio of tributary streams in three different flow periods 102 6- 1 Relationship between % ricefield and pH of tributary streams during the falling limb of the high flow period in the total catchment area 108 6-2 Changes in pH of the Pampanga river during the rising limb of the high flow period relative to the cumulative % ricefield in the total catchment area 109 6-3 Relationship between % ricefield and nitrate-N concentration of tributary streams during the rising limb of the high flow period 110 6-4 Changes in nitrate-N concentration of the Pampanga river during the rising limb of the high flow period relative to cumulative % ricefield in the total catchment area 110 6-5 Changes in ortho-phosphate concentration of the Pampanga river during the rising limb of the high flow period relative to the cumulative % settlement in the 500 m buffer zone along major streams 112 xi Figure page 6-6 Relationship between % woodland and pH of tributary streams during the rising limb of the high flow period in the total catchment area 112 6-7 Changes in pH of the Pampanga river during the rising limb of the high flow period relative to cumulative % woodland in the total catchment area 113 6-8 Relationship between % woodland and nitrate-N concentration of tributary streams during the rising limb of the high flow period in the total catchment area 114 6-9 Changes in nitrate-N of Pampanga river during the rising limb of the high flow period relative to the cumulative % woodland in the total catchment area 115 6-10 Relationship between % grassland and pH of tributary streams during the rising limb of the high flow period in the 500 m buffer along major streams 115 6-11 Changes in pH of the Pampanga river during the rising limb of the high flow period relative to cumulative % grassland in the 500 m buffer zone along major streams 116 6-12 Relationship between % grassland and nitrate-N concentration of tributary streams during the rising limb of the high flow period in the 500 m buffer zone along major streams 116 6-13 Changes in nitrate-N concentration in the Pampanga river relative to the cumulative % grassland during the rising limb of the high flow period in the 500 m buffer zone along major streams 117 6-14 Changes in ortho-phosphate concentration of the Pampanga river relative to cumulative % lahar covered areas during the falling limb of high flow period in the 500 m buffer zone along major streams 118 6-15 Changes in TDS concentration of the Pampanga river relative to cumulative % lahar covered areas during the falling limb of the high flow period in the 500 m buffer along major streams 119 6-16 Changes in COD concentration of the Pampanga river relative to cumulative % lahar covered areas during the falling limb of high flow period in the 500 m buffer zone along major streams 120 6-17 Distribution of commercial hog farms in the Pampanga river basin 122 6-18 Distribution of commercial poultry farms in the Pampanga river basin 124 6-19 Distribution of commercial large ruminant farms in the Pampanga river basin . . 125 6-20 Distribution of commercial small ruminant farms in the Pampanga river basin. . . 126 6-21 Relationship between AUE density and nitrate-N concentration of tributary streams during the rising limb of the high flow period in the 500 m buffer zone along major streams 128 Xll Figure page 6-22 Changes in nitrate-N concentration of the Pampanga river during the rising limb of the high flow period relative to the cumulative A U E density in the 500 m buffer zone along major streams 128 6-23 Changes in nitrate-N concentration of the Pampanga river during the rising limb of the high flow period relative to the cumulative human population density in the 500 m buffer zone along major streams 134 6- 24 Distribution of 1990 human population in the Pampanga river basin 133 7- 1 Simplified nitrogen model 138 7-2 Distribution of expected total nitrogen concentration in runoff of the different catchments in the Pampanga river basin 149 7-3 Effect of increasing animal production on nitrate-N concentration of streams in the Pampanga River Basin 153 7- 4 Effect of decreasing agricultural farms on the nitrate-N concentration of streams in the Pampanga River Basin 154 8- 1 Distribution of Barangay Captains who answered questionnaires 157 xiii L I S T O F A B B R E V I A T I O N S A B C Association of Barangay Captains A P H A American Public Health Association A U E Animal Unit Equivalent BAS Bureau of Agricultural Statistics BOD Biochemical Oxygen Demand CARP Comprehensive Agrarian Reform Program COD Chemical Oxygen Demand B S W M Bureau of Soils and Water Management CENRO Community Environment and Natural Resources Office CFIC Central Fermentation Industries, Incorporated E C A Environmentally Critical Areas E M B Environment Management Bureau EMPAS Environmental Management and Protected Areas Sector EQD Environmental Quality Division FEACO Far East Alcohol Company D A Department of Agriculture D A R Department of Agrarian Reform DPWH Department of Public Works and Highways DILG Department of the Interior and Local Government DO Dissolved Oxygen DOH Department of Health DOTI-NE Department of Trade and Industry-Nueva Ecija DP Development Plan E T N Expected Total Nitrogen ESRI Environmental Systems Research Institute GIS Geographic Information Systems H L U R B Housing and Land-use Regulatory Board IDP/NE Integrated Development Project-Nueva Ecija IFDC International Fertilizer Development Centre IRRI International Rice Research Institute L G C Local Government Code L G U Local Government Units LREP Land/soil Resources Evaluation Project M P D C Municipal Planning and Development Coordinator N A M R I A National Mapping and Resource Inventory Authority NCSO National Census and Statistics Office N E D A - C L National Economic and Development Authority (for Central Luzon) NIA National Irrigation Administration N P C C National Pollution Control Commission NPEC National Protection Environment Council NPS Non-point Source ONN Observed Nitrate Nitrogen P A G A S A Philippine Atmospheric, Geophysical, Astronomical, Seismologic, Authority L I S T O F A B B R E V I A T I O N S P.2 PD Presidential Decree PENRO Provincial Environment and Natural Resources Office PFP Physical Framework Plan PHILRICE Philippine Rice Research Institute PLUC Provincial Land-use Council PNN Predicted Nitrate Nitrogen PPDO Provincial Planning and Development Office PPFP Provincial Physical Framework Plan ppm parts per million ppT parts per thousand RDC Regional Development Council RTD Regional Technical Director TDS Total Dissolved Solids UPRP Upper Pampanga River Project UP-STJRP University of the Philippines-School for Urban and Regional Planning USAID United States Agency for International Development USDI-BOR United States Department of the Interior-Bureau of Reclamation XV A C K N O W L E D G E M E N T I would like to thank the following for their contribution in the attainment of my doctoral degree: The Canadian International Development Agency (CIDA) through the Environment and Resource Management Project (ERMP) of the School of Resource and Environmental Studies (SRES) of Dalhousie University and the Institute of Environmental Science and Management (IESAM) of the University of the Philippines at Los Banos, for funding my doctoral studies; special thanks to Peter Guy, Nick Briones, Jennifer Leith, Teresa Janik and the rest of the ERMP staff for administering my fellowship; To the Tarlac College of Agriculture (TCA), through Dr. Feliciano Rosete and Dr. Priscilla Tangonan for allowing me to take a leave from the college to pursue my degree; To the Resource Management and Environmental Studies (RMES) department, for the additional research funding; the RMES staff including Nancy Dick, Sandra Brown, Wayne Tamagi, Alice Kenney, and Yao Cui, for their support during the preparation of the thesis; To Sylvia Leung, Maureen Evans, Gilles Galzy, and Luz Aquino for their help in my stay at the Animal Science Department; To Dr. Richard Beames for his supervision during my first few years at UBC, and for his patience in waiting for me to finish my degree; To Dr. Ken Hall for his questions and comments which made a difference in the content of the manuscript; To Dr. Les Lavkulich for his encouragements and faith that I can finish a Ph.D.; To Dr. Hans Schreier, my research supervisor, who patiently guided me to the finish line both academically and financially; and To my family and friends who were a source of support and understanding during my years at UBC. MARIANO C. MAPILI, JR. 1 Chapter 1. INTRODUCTION 1.1 The issue: changing land-use and water quality-emerging threats to the sustainability of agriculture in the Philippines The Philippines is striving for economic development to keep pace with the global economies, especially those of its South East Asian neighbours. As a major factor in its development, land and water resources management are critical issues, as the major sectors of its economy - agriculture and the predominantly agri-based industry, rely heavily on these resources. The conditions of these resources in terms of quantity, quality, and spatial distribution are therefore of utmost importance as they may limit the magnitude and sustainability of economic development in the country. In recognition to the fact that the country's population derives its economic life blood essentially from agriculture, the Philippine government has prioritized the development of the agriculture sector in order to increase food production. However, this sector has not kept pace with the food requirement of the growing population, as indicated by the declining production figures in the main agricultural products- rice and fish (Provincial Development Reports, 1992), the country's staple foods and barometers of its economic development. There are now indications that the poor management of land and water resources is one of the contributing factors to this situation. In the case of rice production, in spite of improved technology, agrarian reforms, massive irrigation systems, and other approaches, the Philippines has not achieved its target of rice self-sufficiency, and remained an importer of rice (Salita, 1974; Barker et al, 1985; and Herdt et al, 1987). There are several factors responsible for this situation, but recently, the rapid conversion of agricultural lands to other uses has been commonly cited as matter of concern both by the Department of Interior and Local Government (DILG) and the National Economic and 2 Development Authority (NEDA) in 1992 (DILG, 1992 and RDC, 1992), although no data were cited to support the rhetoric. In terms offish production, there is concern that the low harvest, especially for inland fish production, is due to the effect of water pollution, as fishermen have reported to the Philippine Journal (1994); Malaya (1994); Philippine Daily Inquirer (1994), among other major mass media in the country. The Department of Environment and Natural Resources (DENR) in 1990 attributed the water pollution to the different land-uses in the upper catchments of rivers that feed the fishponds with water. Among these land-uses was agriculture. Land-use problems are closely linked with water quality problems. In the Philippines, for example, although there is a dearth of studies on the interaction between land-use and water quality, there are also indications that this interaction exists. For example, among the land-uses suggested as polluting to the fisheries by the DENR was agriculture (DENR, 1990), but at the same time the National Irrigation Administration (NIA) in its survey of the extent of pollution in irrigation systems throughout the country, cautioned that water pollution of streams is on the rise, blaming animal farms and food processing industries, as the major sources of pollution (Santos et al, 1986). In order to solve both land-use and water quality problems therefore, there is a need to understand their interactions. Initiatives to solve the land-use and water quality problems have recently been announced. The Provincial Physical Framework Plan (DILG, 1992) hoped to curb agricultural land conversion and preserve environmentally critical areas. In terms of water pollution, especially non-point sources (NPS) such as the case of agriculture, which pose a difficult problem because of the difficulty in monitoring, the solicitation of the barangay's involvement in problem identification and enforcement has been a new initiative (Feliciano et al, 1992). This initiative follows after the regulation of land-use, or "watershed management" which has emerged as the principal tool for 3 protecting water quality in the U.S., where the regulation of NPS occurs primarily at the local level (Nash, 1993). There is a need to determine the potential of the barangay in this initiative, but it must be recognized that its involvement is a critical component in solving water quality problems that has been overlooked in the past. There is a need to understand the dynamics between land-use and water, and examine their transformations, and trends in both because they affect agricultural sustainability1 in the Philippines. In the agricultural region of Central Luzon, farming and fishing, the primary industries, are both at risk from, and therefore the lifestyles of the farmers and fishermen may be threatened by, changing land-uses and water quality. Not only are agricultural farms disappearing at a rapid rate, but cities pose a threat to the lifestyle of farmers and fishermen, through water pollution, as well as losing water supply in favor of the urban areas. As Postel (1993) verified "where water scarcities and competition for water exists between cities and farms, typically farms lose water". Overall, the need for a new approach to land-use and water quality planning and management represents the emphasis of this research work, and implicit within this is the essential role of government institutions. Likely, the approach employed through the framework developed in this research will further the understanding of the problems, interactions between, and initiatives on, land-use and water quality, which may affect farming and fishing. A case study was undertaken in the Pampanga River Basin, one of the two river basins comprising the "rice granary" of the Philippines, where a historical study of changes in land-use and water quality in the basin 1 Agricultural sustainability is used here in die context of the three major school of thoughts on agricultural sustainability as reported by Senanayake (1991). Thus, under Philippine conditions, land-use and water quality affects sustainability of agriculture, when the supply of food is not enough to meet the demand of the population (productivity school); when land-use and water quality affects the quality of the environment (stewardship school); and when the quality of life is threatened (community school). 4 answered questions such as: What was the past condition? How and why did it get to be what it is now? and What implications will it have for the future? An emerging tool that has great potential in formulating environmental and resource management scenarios and strategies is the Geographic Information Systems (GIS) approach. This technique was explored as a utility function to form the focus for analysis and data presentation of bio-physical as well as socio-economic considerations, as its usefulness to natural resources and environmental research has already been proved by researchers such as Fox et al, 1993; He et al, 1993; Kind et al (1993); Philips and Barbrick, 1993; Rains and Latham, 1993; Robinson and Ragan, 1993; Schreier et al, 1994; and Wong (1993), among others. 1.2 Research Goal The goal of the present research is to develop a framework by which interactions between land-use changes and water quality, and their interconnected institutional factors (the emerging threats to sustainable agriculture in an agricultural river basin), can be assessed in terms of historic development and projected scenarios, by employing GIS. 1.3. Specific Objectives 1.3.1 To assess historic land-use changes in the PRB; 1.3.2 To relate land-use planning and land-use changes in the PRB; 1.3.3 To assess water quality of the Pampanga River and its tributaries; 1.3.4 To relate land-use and water quality in the PRB; 1.3.5 To develop a framework by which predictions and assessment of water quality under different imposed or implied scenarios resulting from different policy alternatives in the region can be accomplished; and 5 1.3.6 To explore the opportunity for involving the local government (Barangay) in the management of land-use and water quality. 1.4. The Case Study Site: Pampanga River Basin 2 There are several reasons for choosing the Pampanga River Basin as the case study site. First of all, among the agricultural river basins in the country, it has the best hydrology record of any river basin in the Philippines. The basin has remained mainly agricultural for a long time and is just starting to get urbanized. Therefore agricultural development and changes can be traced more accurately. The river basin area occupies half of the Central Plains of Luzon, the rice granary of the country. Furthermore it has been affected by two natural calamities which caused massive land-use changes (an earthquake in 1990 and the eruption of Mt. Pinatubo in 1991). The basin is a representative of what threatens agricultural sustainability in the country, in terms of human and natural factors. 1.4.1 The Physical Environment of the Central Plains The Central Luzon Region is centrally located in the island of Luzon. It is physiographically divided into two geographic units; the Western Cordillera and the Central Plain. The Central Plain, which is situated east of the Zambales mountain range, is the largest level lowland in the entire country. The drainage of the central plain is dominated by two river basins, the Agno and the Pampanga rivers, separated by a low, poorly defined, topographic ridge extending northeast from the province of Tarlac. The Pampanga river basin contributes about 40% of the valley floor known as the Central Luzon Plain. 2 This discussion comes out primarily of reports from the U.S. Department of the Interior-Bureau of Reclamation (1966), Galvez (1977) and Salita (1974) which have always been the major references for later reports and studies on the Central Luzon Region and the Pampanga River Basin. 6 Figure 1-1 shows the location of the basin relative to the country, F igure 1-2 shows the elevation slice map of the basin, and Figure 1-3 shows the major tributaries of the Pampanga river in the basin. The river is formed by the Carranglan and Pantabangan rivers, (the latter has been converted into the Pantabangan reservoir in 1977) in the Caraballo Mountains of Nueva Ecija. From here it flows in a southerly direction to its mouth in Manila Bay. Stream gradients in the upper reaches of the river are steep and the valley sections are very pronounced. Upon emerging on the Central Luzon plain near the town of Rizal, Nueva Ecija, the stream gradients become flatter as the river progressively passes through a rich agricultural region, through extensive swamplands and finally into an area of commercial fishponds where the main channel divides into numerous channels to form a network of sluggish tidal streams which eventually find their way into Manila Bay. Mount Arayat, an extinct volcano, is a distinct physical feature in the south-central part of the area. It rises about 1000 meters above the surrounding area. To the east of Mt. Arayat are depressions known generally as the San Antonio and Candaba swamps; the latter is the largest inland swamp in the country. Due to their low elevation, they become discharge points of groundwater in the basin during the wet season. Pampanga river finally flows into commercial fishponds in Bulacan, where the main channel divides into several smaller channels, forming tidal streams which eventually reach Manila Bay. 1.4.2 Climate The basin is characterized by two pronounced seasons consisting of a dry season during the months of November through April and a wet season during the months of May through October. The mean annual rainfall varies from less than 2000 mm (80 in) in the central part, to more than 4000 mm (160 in) in the northwestern part. About 90% of this annual precipitation generally occurs during the southwest monsoon, with most of the precipitation occurring in the Figure 1-1. Location Map of the Pampanga River Basin P a m p a n g a R i v e r B a s i n Figure 1-2. Elevation slice map of the Pampanga River Basin 9 Figure 1-3. The Pampanga River and its Tributaries Ta la vera River Hog Baliuag Benituan river Rio Chico Grande Sacobia River Maasim River PAMPANGA RIVER at Sulipan, Apalit Carranglan River Pantabangan Reservoir PAMPANGA RIVER at Rizal, Nueva Ecija Digmala river Coronel River Cabu River Santor River Penaranda River Madlum River Garlang River I Pampanga River Mainstem I Tributary Catchment Boundary 10 month of August. Rainfall variation in the basin may be attributed primarily to the shielding effect of the topographic relief surrounding the basin upon the water-bearing seasonal winds. The Caraballo mountains in the north and northeast shield the basin from the northeast monsoon from October to January. The Sierra Madre mountains on the east shield the basin from the east trade winds from February to April. The Zambales mountains on the south shield the basin from the southwest monsoon from May to October. This shielding effect accounts for the higher precipitation in the mountainous areas surrounding the basin and the lesser amounts in the central part of the area. Temperature differentials within the basin are relatively small. A mean temperature of 27° C is common in the area and the average relative humidity varies from 75% in the lowlands to about 85% in the mountains. 1.4.3 Soils and Agricultural Economy Fertile alluvial soils derived from the mountain ranges flanking the plains make up the soils of the Central Plains, while ricefields have poorly drained soils, usually with a clay texture. The subsoil, 30 to 60 cm deep, is a compact clay pan of very low permeability. This property considerably reduces the natural drainage capability of the overlying soil and makes it suitable for rice production. Gently sloping upland areas adjacent to the lowlands are devoted to other crops such as sugarcane and vegetables. These areas have more or less friable, well-drained soils. As early as 1960, when a survey was undertaken by the U. S. Bureau of Reclamation, it was already recognized that agricultural development in the basin has reached a stage of relative stability. Virtually all land suitable for cultivation in the plain have been farmed, although a substantial part of the agricultural production occurs only during the wet season. This pattern remained to the present time since no new lands suitable for cultivation was allowed to be converted to agricultural crops. It was the opinion of the researchers that increased agricultural 11 production within the basin would largely be obtained by intensifying the use of present farm lands by irrigation. The total area suitable for irrigation consists of 508,000 ha without limitation, 208,000 ha limited due to soil type, and 109,000 ha with topographic limitations. In 1983, the total irrigated area in the region was 255,830 hectares, which is about 50 % of the irrigable areas. As the most extensively cultivated part of the Philippines, it produces about one third of the total rice harvest of the country. A l l of the five provinces with areas contributing to the plain are rice producing regions with the province of Nueva Ecija as the leading producer. Rainfall is erratic as to time and place of occurrence, but it is generally adequate to produce crops during the wet season, although a deficiency usually occurs during the dry season. As a result, the agricultural practice is to farm the land during the wet season but allow it to lie idle during the remainder of the year even if other climatic factors are conducive to year-round agricultural production. It is with this background that the Upper Pampanga River Project was established. 1.4.4 Human population Figure 1-4 illustrates the changes in population in the basin in three different years from census data (NCSO, 1970, 1980, 1990). As can be observed, the total population has increased over time, however, the growth rate has been declining from 3.65% in 1970, to 2.88% in 1980 and to the present 2.58%. The Central Luzon Region has been cited as having one of the fastest growing populations in the Philippines, with an annual population growth rate which is higher than the country's average, and having the highest population density outside of the National Capital Region (RDC, 1992). The environmental problems in the region has been attributed largely to this high population density and growth rate (RDC, 1975). 13 1.4.5 The Upper Pampanga River Project (UPRP): the promise of a technical fix The UPRP is the largest multipurpose water resource development project in the Philippines (Dixon, 1989). It harnesses the irregular flows of the Pampanga river for irrigation and power generation. The U.S. Department of Interior's Bureau of Reclamation surveyed all river basins in the country and conducted several feasibility studies in the early 1960's. The bureau commissioner in November of 1966, in a letter to the Director for US AID stated that because of the serious deficiency in agricultural production that exists in the Philippines it had assigned priority to the use of water for irrigation and that it recommended the immediate construction of the Upper Pampanga River Project. This recommendation was made regardless of their recognition that the basin as a whole does not have the ideal physical characteristics for multipurpose river development. The steeply rising mountains that surround the basin have short, high gradient streams with only a few potential reservoir sites of limited capacity and small upstream drainage areas. Only because of the very high rainfall in the mountainous areas does sufficient water becomes available for economic development of river regulation structures. Furthermore, the basin is also beset with very complex geologic problems, as earthquakes occur at frequent intervals; active volcanoes are nearby; major faulting is prevalent; and conditions in the mountains are conducive to earth and rock slides. Yet the advantages, they concluded, outweighed the above-mentioned drawbacks. The first and foremost reason for the project was irrigation. The bureau recognized that the economic and social welfare of the basin is directly related to the development of its water resource. The second reason for the reservoir's construction was flood control. During the normal annual cycle of flow conditions the Pampanga and its tributaries overflow their banks and flood adjacent lowlands. The third reason for the construction of the dam was hydroelectric power 14 generation. The reservoir water releases need to satisfy irrigation requirements, hydroelectric power generation, and flood control, particularly during the wet season. Studies showed that the generation of firm hydroelectric energy would materially reduce the quantity of water for irrigation during the dry season. Also, factors such as fish conservation, navigation, and reservoir construction for drinking water supplies, were not given adequate consideration. Despite the initial success of the UPRP, it was not able to keep pace with the growing water demand for irrigation and electric power generation. The reservoir has only been full once since its establishment, and the government is now actively contemplating the construction of the Casecnan Project, a trans-basin water transfer system (Tolentino, 1993: Personal Communication). This would involve the construction of a storage reservoir on the Casecnan river (in another basin), and a tunnel which would bring water to the existing Pantabangan reservoir 1.4.6 Study site boundary For the purpose of the study, the basin encompasses the drainage area of the whole Pampanga river and its tributaries up to the river's section in Sulipan, Apalit. With this boundary, the study basin has a total area of 811,110 hectares. This boundary was chosen because further downstream from Sulipan, the river branches not only into several braided streams but also into canals and floodways. This makes the assessment of the contributing catchment areas less accurate. The study basin is therefore bounded on the east by the Sierra Madre mountain range; in the north by the Caraballo mountains; on the west by a less defined ridge in Tarlac and Mt. Pinatubo; and to the south by Mt. Arayat and the banks of Pampanga river to its mouth in Sulipan, Apalit. 15 1.5 Review of Previous Land-use and Water Quality Work in the Pampanga River Basin No study or report was found about changes in land-use in the basin, or for the whole Central Luzon area. Although there were scattered reports on land-uses in the whole region, land-use classifications have not been consistent, making it impossible to compare data between reports. For example, the closest comparison would be between the 1960 data presented by Sandoval and Mamaril (1970) and the report of the U.S.D.I. Bureau of Reclamation. Both data sets have land-use classifications that are similar, but the total areas for each of the evaluated province differed by as much as 44%. Later reports were more concerned with the agricultural areas and therefore the classifications changed. This present study is the first to quantify the rates of land-use changes in the basin. Its usefulness for better policy decision making in land-use planning and related fields cannot be over emphasized. A search for hydrology and water quality data on the Pampanga river yielded only a few studies, and indicated that the river has been studied to determine its usefulness for irrigation but not drinking water supplies. This narrow objective is reflected in the water quality variables measured. Simsiman and Galvez (1962) took 116 surface water and 10 groundwater samples in the Pampanga river in both the dry and the wet seasons in 1961. Bautista (1964) collected more irrigation water samples (447) from Pampanga and Laguna de Bay from Oct. 1961 to June 1963. In both studies water quality parameters sampled were electrical conductivity, Total Dissolved Solids (TDS), pH, Ca, Mg, Na, K, C 0 3 , H C 0 3 , nitrates and chlorides. Both studies concluded that the water was safe for irrigation. The same conclusion was reported by USDI-BOR (1966) and NLA (1977), although data were not found in these reports. Galvez (1977) mentioned that N P C C (1967) classified the Upper Pampanga river in the province of Nueva Ecija as class A and the 16 lower end in the province of Pampanga as class C, but the data used for the classification were not provided Lidngson (1976) carried out the most comprehensive water quality investigation in the basin and therefore deserves more attention. In her study, atmospheric reaeration was identified to be the major contributing factor for dissolved oxygen to the reservoir water. The available and collected water-quality data in the reservoir and streams of the UPRP indicated a spatial variation in salinity level from as low as or less than 100 ppm in the headwaters to a high of 300 ppm in the outflows from the irrigation service area. In terms of seasonal variation, the researcher observed that TDS values in the wet season were less than those in the dry season due to dilution, and for Biochemical Oxygen Demand (BOD 5), the values ranged from 0.2-3.4 mg/1 during the dry season from January to April 1976 to 0.1-4.0 mg/1 in the wet season month of July 1976. The study also found nitrate-N concentration to vary from trace to less than 3 mg/1 and phosphate-P concentration to range from 0 to 0.44 mg/1. She concluded that nitrate, rather than phosphate, is the more limiting nutrient affecting the viability of the reservoir water for fishery development. No follow-up of Liongson's work, and no correlation of water quality with land-use were conducted since the late 1970's. The literature on land-use is severely lacking, while that for water quality is fragmentary. Although the latter data have been used to compare the relative long-term temporal changes in water quality, there is a great dependence on the data generated from the present study to achieve the goals and objectives set forth earlier. 17 1.6 A Contribution to the Understanding of Land-use and Water-Quality Interaction in the Philippines The interdisciplinary nature of the research, the lack of consistent land-use and water quality studies in the basin, as well as the absence of any study that links the issues of land-use, land-use planning, water quality, and related institutional arrangements in the Philippines, called for the use of diverse methods in the conduct bf the research. The methodology which is divided into three main groupings will be discussed in Chapter 2, while the succeeding six chapters will be devoted to the discussion of results. In Chapter 3, the land-use changes in the basin were evaluated for three different years (1953, 1980 and 1993). A more detailed study on land-use changes in the province of Nueva Ecija between 1988 and 1993 will be discussed in the same chapter, to elucidate changes in irrigated and rain-fed agriculture. The basin-wide and provincial studies will both reveal that conversion of agricultural lands in the basin is not compatible with sustainable agriculture. Through the review of development plans of the primary planning agency in the region, the link between the problems in land-use planning with the land-use changes that occurred, will be discussed in Chapter 4. The evaluation of a provincial land-use planning initiative of the province of Nueva Ecija will be presented in the same chapter to provide an insight and overview of the present land-use planning process in the region. A comparative analysis of the proposed plan and the existing land-use that indicates the need to improve the proposal i f future sustainability of agriculture in the basin is to be achieved, will be discussed. An assessment of the water quality of the Pampanga river and its tributary streams will be discussed in Chapter 5. The assessment will be explained in terms of spatial and temporal variation of selected water quality parameters. The results will be compared with data from other rivers in the country that are considered polluted. The DENR has been preoccupied with 18 examining the water contamination problem and they suggested that the different land-uses in the basin are the likely cause of the problem. This interaction between land-use and water quality in the basin is the theme of Chapter 6. The discussion will draw upon the empirical relationship between the land-uses presented in Chapter 3 as an index of pollution, and the water quality assessment discussed in Chapter 5. Through correlation and trend analyses, it will be revealed that different land-uses, including different species of animals, in different areas are affecting the water quality of streams at different flow periods. Nitrate-N had the strongest relationship with land-use, and this will be the subject Chapter 7. A simplified nitrogen budget was used to determine key surplus nitrogen areas and with this, different management strategies (scenarios) can be examined. Land-use and water quality problems have been traditionally approached primarily at the regional, and to some extent at the provincial level of government. However, there are now measures to look to the local government for solutions. The role of the local government (barangay) in the management of land-use and water quality will be explored in Chapter 8. It will show that the involvement of the barangay in the management of land-use and water quality will be useful in an effort to reduce the conflict and environmental problems. Chapter 9 will present summaries, conclusions, and recommendations that are helpful in improving the management of land-use and water quality in the basin. Chapter 2: METHODS The data base used in the study, which came from various sources, was obtained through the use of diverse methods. Water quality parameters were measured in the field; socio-economic data and maps were acquired from several local, regional, and national government agencies; while information for institutional analysis were gathered through interviews, questionnaires and government reports. 2.1 Field Method The field method refers to the sampling of streams for water quality, which was conducted from November 1993 to July 1994 (inclusive). The following describes the method used in this sampling process. 2.1.1 Parameters Measured The land-uses and activities in the study area were described earlier as mainly agricultural; therefore the water quality problems are expected to be caused mainly by nutrients (Nash, 1993). Thus, the essential water quality parameters measured to reflect pollution were Dissolved Oxygen (DO) and organic matter measured as Chemical Oxygen Demand (COD), as well as N (in the form of nitrate) and P (in the form of ortho-phosphate). These same parameters were measured by Sussmann (1983); Stehfest (1978); and Overcash et al (1983), to examine agricultural pollution. Additional water quality parameters were measured, including pH, TDS, and water temperature, as they may affect the transformation of nutrients in the land and in the water. 20 Ittrsitu Measurements A Cole-Parmer Standard Water Analyzer was used to measure four water quality properties. The Analyzer uses one probe to measure pH, TDS, temperature, and DO, simultaneously. The analyzer, after being calibrated in the field, was immersed into approximately three-fourths depth of the stream, and the values of the four parameters displayed by the hand-held meter were recorded. Table 2-2 presents the ranges and detection limits of the different modes. Aside from the values recorded from the analyzer, the % saturation of oxygen in streams was calculated by dividing the observed concentration of DO by the extrapolated published values from A P H A (1985) of the solubility of oxygen at different temperatures. This was necessary to allow for the comparison of DO in streams with different temperatures. Nitrate, Phosphate and COD. Grab samples were taken from the stream by using an insulated dipping bucket with a small hole inlet which was submerged in the stream at depths approximately three fourths of the stream's total. Two samples were drawn out from the bucket and placed into two previously cleaned sample bottles. The samples were then placed in a thermochest containing ice as refrigerant. After a group of stations were sampled, the samples were taken out and analyzed using Hach reagent pillows and employing Hach's recommended procedures (Hach's DR/2000 Manual, 1990). Table 2-2 presents the ranges and detection limits of the three chemical tests. The Cadmium Reduction Method was employed for nitrate-nitrogen determination. The Hach Spectrophotometer DR/2000 was set to 500 nm wavelength. A 25 ml sample cell was filled with filtered sample and used to give a 0.0 reading on the spectrophotometer. Another 25 ml sample was added with the contents of one NitraVer 5 Nitrate Reagent Powder Pillow. After 21 shaking and a five-minute reaction time, the spectrophotometer readings in terms of mg/1 of nitrate-nitrogen were recorded. For reactive phosphate (ortho-phosphate), the ascorbic acid method was employed using the same spectrophotometer, and the steps followed are very similar to those of the nitrogen procedure, except that in this case, 890 nm was used as the wavelength and PhosVer 3 was used as a reagent pillow. In the case of COD analysis, a digestion method was first performed. Samples and a blank of deionized water (2.0 ml each) were added to Hach COD reagent vials. After capping and mixing, the vials were heated for 2 hours in a Hach COD reactor which was pre-heated to 150°C. After mixing and cooling, the vials were read in the spectrophotometer at 620 nm wavelength. Table 2-2. Range and resolutions for the different parameters measured Parameter Range Detection Limit pH (pH units) Oto 13 0.01 TDS (ppm) 0 to 1000 1 DO (ppm) 0 to 20.0 0.1 temperature (°C) 0 to 50.0 1 nitrate-N (mg/1) Oto 30 0.1 ortho-phosphate P (mg/1) 0 to 2.50 0.01 COD (mg/1) 0 to 1500 1 2.1.2 Water Quality Sampling Stations fWOSS) The WQSS for the study were selected to be near gauging stations, to enable the future calculation of nutrient loadings (Ward et al, 1990; and Schouter, 1983). The preliminary selection of sampling locations was executed by the process of eliminating stations from the potential list of 58 stream-flow gauging stations reported and used by Galvez (1976). 22 A system of designating a hierarchy of stations, developed by Sanders et al (1990) for monitoring purposes, was used as the criterion of elimination. Following this system, all the candidate stations were marked onto the stream network of the N A M R I A 1980 Topographic Map. A l l candidate stations (both mainstem and tributaries), were assigned integers in sequence based on their relative position to the direction of flow of the Pampanga river mainstem (first number for the upstream station to the last number for the downstream station). The most upstream station, and the most downstream stations, along the mainstem were designated as having the highest rank in the hierarchy. The station with the next rank was selected by adding the lowest and highest numbers, and dividing the sum by two. The station which matched, or was nearest to the resulting number, was designated as the centroid station with the next highest rank. Within the resulting two subdivisions, this procedure was followed to designate the two stations with the next highest ranks, and the same procedure was duplicated for the four resulting subdivisions, and then to the next resulting subdivisions until all the stations have been ranked. However, some of these stations had become inaccessible during the rainy season, leaving only 39 stations to be used in the analysis. 2.1.3 Sampling frequency and strategy The determination of the number of samples required was based on a specified confidence interval about the mean of the variable under consideration, as explained by Nelson and Ward (1981) and Sanders et al (1990). Since this required that the variance of the sample mean be known, and such variance cannot be determined from the fragmented and quite incomplete existing data on water quality parameters for the basin, the data on water flow were used as surrogate data. It was assumed here that the change in water flow is the major factor affecting the variation in the concentration of the water quality parameters, as stressed by Canter (1985). Feher (1983) referred to a comprehensive study of Heck (1981), and concluded with a statement on the linear relationship 23 between water flow and quality. It is assumed further that the variance (of the water flow) had not changed with time, and therefore, the simplest approach (that of using historical data for determining variance) was employed, resulting in a sampling frequency average close to frequencies in the literature such as that of Sussmann (1983). A weekly sampling frequency was chosen, but in the field there were unexpected circumstances such as roads being unpassable at times, break-down of the vehicle, stream drying up, and some stations becoming inaccessible. The final frequencies of sampling is illustrated in Figure 2-1. The strategy for sampling involved the division of the stations into three groups based on their location relative to the road networks, since all the stations could not be sampled in one day. In one sampling day, one group was sampled starting with the station which was most downstream ending at the station which was most upstream. The same procedure was followed for another group in the next sampling day. The sampling dates and observations arranged in chronological order are presented in Appendix Table 2-la. Figure 2-1. Frequency of sampling for each station (Sampling period from November 1993 to July 1994) 50 E fllU) ll l,l ll nil ll 111] lull), ->-1-[.-»-»-i-.-i.-li.-i lj lj lj ll lj lj lj ll lj l l lj tj I 4 7 10 12 14 17 19 27 30 32 36 39 42 44 46 49 51 53 55 57 s t a t i o n s 24 2.2 Surveys, interviews, and reports Since the focus of the study is on the holistic perspective of land use and water quality problems in the watershed, a series of surveys of the government agencies, from the village level to the regional agencies, was undertaken. To gather data on water quality and land use, and to incorporate real-world experience and perceptions of the environment into the analysis, the land-use and water-quality problems and practices were examined in the field and through interviews. There were two visits to the study site. The first visit was exploratory and took place May to August 1992. The second visit, from September 1993 through August 1994, was intensive and comprehensive. The three levels of government in the Philippines are the national, the regional, and the local levels (the last is further divided into the provincial, the municipal, and the barangay governments). The Central Luzon Region (designated as Region III) is one of the 14 regions in the Philippines and is composed of six provinces- Bataan, Bulacan, Nueva Ecija, Pampanga and Tarlac. Unlike the national and local levels where officials are directly elected, the regional level is just an annex of the national government, where functions of the different national agencies are carried out at the regional level. Some of these functions however, are carried out through to the municipal level. In the Central Luzon Region for example, the DENR has regional, provincial, and community (for groups of municipalities) offices. The same is true for the planning functions of NEDA. Because of these many levels of government doing the same functions, it was necessary in the study to survey as much as possible, agencies at all levels of government. The different agencies and offices visited and surveyed are described below, and the data they have provided are summarized in Table 2-3. A list of personal communications is presented in Appendix Table 2-2a, while additional water quality data are presented in Appendix Table 2-3a. 25 2.2.1 Department of Environment and Natural Resources The primary agency of the government responsible for land-use and water quality management is the DENR. Therefore, most of the information for evaluating water quality management came from interviews with DENR officials. At the national level, interviews were carried out with Environmental Management Bureau (EMB) officials to evaluate reports forwarded by the regional office with regard to water quality. The very few reports submitted to this office contained fragmentary data. At the regional level, interviews were carried out with the Technical Director of the Environmental Management and Protected Areas Sector (EMPAS) and the chief of the Environmental Quality Division (EQD), and their staff who carried out water quality monitoring and inspections of regulated point sources of pollution. In the same offices, reports on the polluting industries were copied from existing records. Interviews were also carried out with officials and staff of all the Community Environment and Natural Resources Offices (CENRO) which are the local arms of the DENR. These include Munoz, Talavera and Cabanatuan CENROs in the province of Nueva Ecija, CENRO-Tarlac of the province of Tarlac, CENRO-Angeles for the province of Pampanga, and CENRO-Baliuag for the province of Bulacan. By taking part in the CENRO Cabanatuan's regular inspections of reforestation sites, the researcher was able to visit and evaluate the condition of forest areas beyond some sampling stations in the headwaters. 2.2.2 Planning Offices The National Economic and Development Authority (NEDA-CL), is the regional planning office of the Central Luzon Region while for Nueva Ecija it is the Provincial Planning and Development Office (PPDO). These planning offices were undertaking the first land-use plan and policy project in the Philippines, based at the Integrated Development Project (IDP/NE) office of 26 the province of Nueva Ecija. The researcher participated in the project and therefore gained first-hand experience on the evolution of the land-use plan and policy. At the meetings of the coordinators and at three workshops held for this project, the officials from the Department of Agrarian Reform (DAR), and the Municipal Planning and Development Coordinators (MPDCs), were also interviewed. Table 2-3. Summary of data from government agencies used in the study Source* Data DENR-CL Inspection reports of point sources of pollution in the region DENR-CL Water quality data for Pampanga river and tributaries B S W M Land and resources evaluation reports for all provinces in the region BAS Data on animal population in the region NCSO Census data (human population) in the region N E D A - C L Regional Development Plans PHILRICE Fertilizer application of farmers in the region N E T P P D O Socio-economic data for Nueva Ecija NIA Discharge measurements of irrigation canals and streams P A G A S A Rainfall and discharge measurements for Pampanga River Basin DPWH Water quality data for Pampanga river and tributaries * DENR-CL (Department of Environment and Natural Resources of Central Luzon Region); BSWM (Bureau of Soils and Water Management); BAS (Bureau of Agricultural Statistics) NCSO (National Census and Statistics Office); NEDA-CL (National Economic and Development Authority of the Central Luzon Region); PHILRICE (Philippines Rice Research Institute); NE-PPDO (Nueva Ecija's Provincial Planning and Development Office); NIA (National Irrigation Administration); PAGASA (Philippines Atmospheric, Geo-physical and Seismologic Authority) DPWH (Department of Public Works and Highways) 2.2.3 Barangay Captains The barangay's (village) potential role in land-use and water quality management was determined through the use of structured questionnaires which were written in Filipino (an English translation appears in Appendix 2-4a). Questionnaires were sent to 500 randomly selected barangay captains (village chiefs) throughout the entire basin. This was more than half of the list of the almost 900 total number of active barangay captains provided by the Department of 27 Interior and Local Government (DILG) offices in the four provinces which make up the basin. A total of 172 (34.4%) questionnaires were returned to the researcher. The questionnaire, with three components, evaluated the respondents' perceptions on land-use, water quality and the environment in general. The first component consisted of questions relating to background information of the respondents. The second component relating to the evaluation of the stream closest to their residence, consisted of questions patterned after Coughlin et al (1972). The third component consisted of questioned related to the Local Government Code (LGC). 2.3 GIS and Statistical Analysis All maps used were digitized and analyzed using the Terrasoft Version 10.0 (Digital Resource Systems Ltd.) GIS software, and a summary of the GIS data base is provided in Table 2-4. The 1953 topographic map used was a compilation in 1956 of the interpretation of aerial photographs from 1947 to 1953 by the United States Army. The 1980 topographic map used was the 1990 NAMRIA topographic map which was based on the interpretation of aerial photographs from 1978 to 1980 (Cabanayan, 1993: personal communication). The 1993 land-use map was based on a compilation of control maps of the five CENROs in the study site since the most recent aerial photography of the country is still being undertaken. These control maps have been updated regularly since the projects of the different CENROs were based on the most recent land use in their areas of jurisdiction. Furthermore, officials from these agencies carry out routine inspections and therefore the land uses indicated are therefore expected to be very reliable. The layers derived as a result of digitizing are the primary layers, while combinations and overlays of these layers created the secondary layers which are described in relevant chapters. 28 Data gathered from reports were collated and attached to databases of the layers for municipal, catchment, or barangay centroids, depending on how these were reported. The two functions of Terrasoft that were used extensively are the overlay and buffer functions. The overlay function of the GIS software employing raster themes of the digitized layers with pixel size of 50 meters by 50 meters, was used for land-use change measurement and the production of secondary maps. A buffer is defined as a zone of a specified distance around coverage features and used in proximity analysis (ESRI, 1994; Brown and Schreier, 1992). Buffer analysis is an important tool in the management of, and in showing interactions between, land-use and water quality. In the study, buffer zones were created in Terrasoft by specifying different distances around streams and roads (250 metres, 500 metres, 1000 metres). For example, buffer zones along the streams in the catchment of Station 4, is illustrated in Figure 2-2. In the study, proportions of land-uses within different buffer zones were correlated with the water quality conditions of the streams inside the buffer to determine interactions between land-use and water quality, and to determine where within the basin is water quality most threatened by a certain type of land-use. In the case of buffers on roads, the objective was to determine how land-use has changed along major roads during the years considered in the study. SPSS-PC+ for Windows Version 6.1 (SPSS, 1993) was used in the statistical analysis of water quality parameters (employing Pearson correlation, multiple linear regressions, and analysis of variance tests), as well as in the determination of land-use - water quality relationships (employing correlation and multiple linear regressions). In presenting the trends, Excel (Microsoft, 1990) was used, where, the trendlines may be in linear or quadratic form, depending on their relative correlation coefficients. A nitrogen loading mass balance was formulated based on values from literature and employing a simplified nitrogen budget model. 29 Table 2-4. Summary of maps used in creating the GIS base map Source** Map Use in GIS Primary Layer NAMRIA* 1990 Topographic Map CENRO* N E D A - C L IDP/NE* DENR-CL IRRI /BSWM B S W M 1953 U.S. Army Topographic Map Land-use maps of all CENROs Lahar map Nueva Ecija Land-use Map Nueva Ecija Land-use Plan Cadastral Maps of all municipalities Soils Map of the region Land-use map of Nueva Ecija Soil erosion map of the region Basin Boundary Catchment Boundaries Contours (Elevation) Land-use 1980 Stream Network Road Network Barangay Centroids Land-use 1953 Land-use 1993 Land-use 1993 Land-use 1993 (Nueva Ecija) Proposed Land-use Municipal boundaries Soil texture Land-use 1988 (Nueva Ecija) Soil erosion * NAMRIA (National Mapping and Resource Inventory Authority); CENRO (Community Environment and Natural Resources Office); IDP/NE (Integrated Development Project bf Nueva Ecija) ** For other abbreviations, see Table 2-3. 30 3! Chapter 3: ASSESSMENT OF LAND-USE DYNAMICS IN T H E P A M P A N G A R IVER BASIN: T H E CASE OF T H E E X P A N D I N G AND SHRINKING R I C E G R A N A R Y Striking a balance between the needs of the growing population and the physical base that supports it is the essence of sustainable development. The urgency of this balance under conditions in the Philippines is exemplified by the case of disappearing agricultural lands in the region's major rice growing area, the Pampanga River Basin. In recent years, there has been growing concern that agricultural lands are being converted into other uses at an unsustainable rate (DILG, 1992) although the rate has never been established. The need to preserve agricultural lands in the basin must be based on solid data and information for practicable management solutions, but as it was evident from the exhaustive search for data on land-use in the basin, a severe dearth of materials exists. Thus, there is a need to assess the present land-use in the basin, and to determine the changes that have taken place. 3.1 Land -use changes in the basin 1953 was used as a base year to trace the evolution of land-use changes in the basin. The availability of the 1953 topographic maps of the U.S. Army made it possible to have a land-use evaluation up to this period. The second map used was the 1980 land-use map whiph was reprinted by the National Mapping and Resource Inventory Authority (NAMRIA) and distributed as a reprint 1990 topographic map. The third map was a composite of all the 1993 land-use maps provided by each of the five CENROs in the basin. It was an update based on the 1980 land-use map. A l l maps used and produced were on the same 1:50,000 scale, which is appropriate for a regional assessment. The maps were digitized with Terrasoft Version 10 software. Figures 3-1, 3-2 and 3-3 show the maps for the three different years. 32 Figure 3-1. Land-use evaluation of the Pampanga River Basin from 1:50,000 US Army Topographic Maps of 1953 Pampanga River Basin 1953 Land-use Map • NOT MAPPED 1 0 o 1 0 2 0 TO k m 33 Figure 3-2. Land-use evaluation of the Pampanga River Basin from 1:50,000 N A M R I A 1990 Topographic Maps Pampanga River Basin 1980 Land-use Map 1 0 0 1 0 2 0 10 km 34 Figure 3-3. Land-use evaluation of the Pampanga River Basin from 1:50,000 Nueva Ecija, Pampanga and Tarlac CENROs Pampanga River Basin 1993 Land-use Map 10 1 0 2 0 T O k m N 35 3.1.1 The expansion years: 1953 to 1980 Changes between the 1953 and the 1980 land-use maps were measured using GIS overlay techniques and the results are illustrated in Figure 3-4. As can be observed, the most significant change was the increase in the agricultural land-use, particularly the rice fields, most of which were converted from grasslands and wetlands. This is understandable in light of the fact that at the time, the government was promoting rice cultivation in order to improve self sufficiency to a level necessary to feed the population. It was during this time that the potential of the Central Plains as the rice granary of the country was being boosted. Major investments were made for irrigation and the area received a lot of government attention. For example, Rossell (1955), in his review of irrigation in the Philippines pointed out that of the total 65 irrigation pumps existing in the country, 75 % were concentrated in Central Luzon, an area which is less than 8% of the country. This peculiar distribution was justified in that Central Luzon is indisputably the rice granary of the country, and, for this reason, it was decided that immediate attention to this area was more practical and could contribute greatly to overall rice production, much more than could be reasonably expected from regions farther from the industrial and population centers that are poor producers. Attention also came in the form of the construction of the UPRP project which was completed in 1977. Not only did this project increase food production through increased irrigation, but the conversion of grasslands and woodlands to arable agricultural land had come as an outgrowth. As Dixon (1989) reported, the population has grown, in part because of rapid in-migration associated with the construction activities. Most of the population are now dependent on the rapid land conversion to agriculture for a livelihood on the steeper slopes of the grasslands and the woodlands. The expansion of arable land into wetlands particularly in the Candaba swamp, although not as substantial as that from the grasslands, may have traded ecological stability for production. 36 Figure 3-4. Land-use dynamics from 1953 to 1980. Arrows indicate the net direction and value of change from one classification to another. All percentages are in terms of the total of the common area being compared (boundary of mapped 1953 area). 3.1.2 The vanishing years : 1980 to 1993 GIS overlay techniques were again employed in measuring the changes in land-use from 1980 to 1993 in the basin. The changes that occurred between these years are illustrated in Figure 3-5. As can be observed, the lahar-covered area was included in the classification because of the 1991 Mt. Pinatubo eruption. The consequence to the basin was that hundred of hectares of land was covered by lahar. Although this is a natural occurrence, it was included since it is one of the natural changes that greatly affected the land. All types of classifications were affected by the lahar, but the rice fields in low-lying, prime agricultural lands in the western portion of the basin have been particularly affected. 37 0.1% iRiccficlds - 2 7 % 0.1 % Wetlands + 0.1% Grassland Woodland -6.0% 3.9 % + 37% 1.2 % Settlement + 35% Lahar + 16% 0.1% Figure 3-5. Land-use dynamics from 1980 to 1993. Arrows indicate the net direction and value of change from one classification to another. All percentages are in terms of the total of the whole basin area which is being compared Figure 3-5 shows that aside from the natural changes, the overall arable agricultural land base has decreased by 2.8%. Although most types of land-uses contributed to the growing settlement areas, it was the rice field that contributed the most. Although rice fields are being converted to settlements, this is partially offset by the conversion of grassland to rice field. This latter trend is of concern since the remaining grasslands are on steeper slopes and converting them to rice fields will aggravate the already regrettable state of soil erosion in the basin. Furthermore, these lands are not as productive as those that have already been exploited. Grasslands were subjected to the greatest conversion pressure, and the conversion of grasslands to woodlands was of particular interest, since this is in complete contrast to what happened over the 1953-1980 period. This means that reforestation, which involved community 38 groups for social forestry and contract reforestation may have influenced the increase in forest cover. Although it is not safe to assume that this means an increase in trees, since the 1993 land-use map was based on maps where the success of the reforestation or social forestry projects were not indicated, it is still evident that the forest cover in the basin is on the rise. 3.1.3 Summary land-use changes from 1953 to 1993 Because of the incomplete watershed cover of land-use in 1953, the comparison between the 1953, 1980 and 1993 evaluations needs to be carried out in two steps. However, the trends shown are similar, and therefore changes from 1953 to 1993 can be summarized using the 1953 boundaries. The agricultural land in the basin has increased from 1953, reached a peak in 1980, but has declined since that time as summarized in Table 3-1. It is likely that agricultural land will not increase in the future since most of the lands available for rice farming has already been exploited. Even in 1960, the U.S. Bureau of Reclamation had concluded that most of the areas with suitable soils and slope had been cultivated. It is therefore alarming to find out that in the future, the decline in arable agricultural land may follow this trend which might result in decreased overall production of rice. This might be balanced with increasing production on the same land by technology, such as irrigation. However, there is still the question of whether or not the irrigated fields will also be converted. This question was answered by a case study of the Nueva Ecija Area, discussed in the next section. Settlement areas increased steadily over the years studied. The increase have been consistent with the increase in population. Although all the different land-use classifications have contributed to the increase in settlements, most of it comes from the conversion of rice fields. This is understandable since more people stay and build up settlements in a productive area. 39 Table 3-1 Summary of land-use changes in the 1953 map boundary. Land-use Classifications 1953 1980 1993 Ha % Ha % Ha % Rice fields 287061 45.1 383172 60.2 339890 53.4 Settlements 636 0.1 4455 0.7 35644 5.6 Woodlands 129209 20.3 83381 13.1 99930 15.7 Grasslands 189040 29.7 156579 24.6 137484 21.6 Wetlands 30552 4.8 8911 1.4 9547 1.5 Lahar-covered areas 14003 2.2 Total 636498 100 636498 100 636498 100 The influence of road networks on the increase in settlements was determined through the GIS buffer analysis function. Three different distances (250, 500 and 1000 meters) from the roads were buffered to measure the changes in the percentage of settlement in the overall land-use area. This was followed by GIS overlay techniques on the three buffer zones and the three land-use maps (1953, 1980, 1993). The 1953 boundary was used in the analysis and the resulting data contained in Table 3-2 suggest that there is a strong negative correlation between the settlement area and its distance from the roads. As one goes farther from the roads, the percentage of settlement areas decrease. The increase in settlement areas is consistent with the availability of road networks. The consequence is that rice fields near the roads become the most vulnerable lands to be converted to settlements. In fact this is true in the entire basin, where rice fields have been converted to accommodate built-up areas consisting of buildings, real estate subdivisions, gas stations, food courts, and warehouses. 40 Table 3-2. Percentage of settlement area in three different buffer classifications and years Distance from roads 1953 1980 1993 % % % 250 meters 0.59 11.40 29.02 500 meters 0.36 7.07 19.50 1000 meters 0.17 1.92 10.21 3.2 Food land base and settlements conflict: The Nueva Ecija Area Case Study The land-use classifications based on the topographic maps are quite limited, and to determine recent changes in a more accurate way, a case study in an area with more detailed classification was made. Although the case study site was of a smaller area, the existing land uses are a good reflection of the activities in the whole basin. The case study was undertaken to understand specifically the changes in the food land base, particularly in terms of irrigated and rain-fed rice fields, as well as the vegetable growing and settlement areas. The province of Nueva Ecija was also chosen since almost the whole province is within the basin. The first ever provincial land-use plan and policy in the Philippines was initiated in this province (IDP/NE, 1993). In this study, the Nueva Ecija Area, as illustrated in Figure 3-6, is that area of the province covered in the basin plus some area of the Sierra Madre mountains belonging to the basin. This area was chosen because it encompasses entirely the watersheds within Nueva Ecija, and therefore, this area is larger than the total area of the province. The more detailed land-use map of Nueva Ecija for 1988 from B S W M containing more classifications than the topographic maps from NAMRIA, was used in the study. The other map used was the 1993 land-use map from IDP/NE. Both maps are at a 1:50,000 scale. The maps were digitized and an overlay analysis was done in Terrasoft. As can be observed in Figures 3-7 and 3-8, the former classification of the rice fields was split between the irrigated and the rain-fed Figure 3-6. The Nueva Ecija Area in Relation to the Whole Pampanga River Basin 42 Figure 3-7. Land-use evaluation of the Nueva Ecija Area from 1:50,000 Nueva Ecija CENROs (1993) Nueva Ecya Area 1993 Land-use Map LAND-USE CLASSIFICATIONS M IRRIGATED RICEF1ELDS • RAINFED RICEFIELDS • SETTLEMENTS • WOODLANDS • GRASSLANDS • SUGARCANE FIELDS • VEGETABLE FIELDS • WETLANDS 10 0 10 20 TO km 43 Figure 3-8. Land-use evaluation of the Nueva Ecija Area from 1:50,000 BSWM Land-use Map (1988) Nueva Ecija Area 1988 Land-use Map LAND-USE CLASSIFICATIONS • IRRIGATED RICEFIELDS • RAINFED RICEFIELDS • SETTLEMENTS • WOODLANDS • GRASSLANDS • VEGETABLE FIELDS • SUGARCANE FIELDS B WETLANDS 10 0 10 20 T O Km 44 rice fields, while the former classification of grasslands was divided among pastures, vegetable areas, and sugarcane plantations. Land-use changes between 1988 and 1993 in the Nueva Ecija Area are illustrated in Figure 3-9. What is noticeable in the above illustration is that all the land-use classifications are contributing to the increasing settlement area; however, most comes from the rice field classification. The conversion rate of irrigated rice land to settlement is twice the rate of the conversion of rain-fed agricultural land to settlement. The reason is that irrigated areas were more accessible to roads and thus were more easily converted to settlements. Another possible reason is the fact that irrigated areas would generate more income due to higher production. Therefore, these areas have a greater tendency to become settlements than those less productive rain-fed areas. Ir i igaicd Figure 3-9. Land-use dynamics from 1988 to 1993 in the Nueva Ecija Area. Arrows indicate the net direction and value of change from one classification to another. All percentages are in terms of the whole area being compared. 45 In any case, converting the rice fields to settlements is counter-productive to the attainment of self-sufficiency in rice, since the food land base decreases permanently once it is converted to settlements. This problem is exacerbated by the fact that it is the irrigated fields which are most vulnerable, the fields which were counted on by the government for increased production. If this process continues, the shrinking food land base would only worsen the food shortages the country is already experiencing. It is in the context of preserving the food land from the encroaching settlements area that the Nueva Ecija Land-use Plan and Policy of 1994 was initiated. The evolution of the plan and policy is discussed in the next chapter. The loss of rain-fed rice field and vegetable growing areas had been alleviated to a certain extent by the conversion of grasslands to agricultural areas. However, the grasslands are not only under enormous pressure from the arable agricultural land expansion but from the settlements and woodlands development as well. Grasslands that came from woodlands are now being converted back to woodlands through reforestation. The grasslands are shrinking in size and their other uses are therefore being compromised. Table 3-3 summarizes the land-use dynamics in the Nueva Ecija Area. Expansion of irrigated rice fields peaked in the late 1980's, but has now started to decline. It is anticipated that further decreases will occur in the near future due to population expansion. Rain-fed areas are not affected to the same extent because they still have the grasslands to fall back to, while irrigated areas have consistently been exploited, since the early 1970's. 46 Table 3-3 Summary of land-use changes in the Nueva Ecija Area Land-use Classifications 1980 1988 1993 % % % Rice fields Irrigated 28.5 26.5 Rainfed 14.6 16.2 Sub-total 49.6 Settlements 0.6 2.1 4.6 Woodlands 23.6 26.2 27.2 Grasslands Pasture/meadows 26.0 22.3 Sugarcane fields 0.1 0.1 Vegetable areas 1.3 1.9 Sub-total 25.2 Wetlands 1.0 1.2 1.2 Total 100 100 100 3.3 Unsustainable changes in the land The data in this chapter revealed that the agricultural lands in the basin, which used to not only support the basin population but also people in other regions, are declining. Population, on the other hand, is still increasing. The balance between population and food production is becoming more and more difficult to achieve, even with help from technological innovation. Land conversion, particularly agricultural land conversion in the basin is not consistent with sustainable agriculture. Consequently, there is a need to understand the causes and provide solutions to this problem before a plan to sustainable development can even be formulated. This need is the theme of the next chapter. 47 Chapter 4: LAND -USE PLANNING AND M A N A G E M E N T IN T H E P A M P A N G A R I V E R BASIN: P R O B L E M S AND INITIATIVES The preceding chapter revealed that increases in human population in the basin have had a drastic impact on land-use. To understand how these changes came about, it is necessary to determine how land-use and land-use planning have been treated in the region in the past. Also, in order to improve land-use planning, the process of arriving at a land-use plan and policy has to be analyzed. The relationship between land-use planning and land-use is the theme of this chapter, and is divided in three parts. First, a discussion is presented on land-use planning from a review of the Development Plans (DP) of the N E D A, which is the regional planning agency. This discussion traces the evolution of land-use planning in the region and presents factors that might have affected the land-use changes presented in the preceding chapter. The fact that land-use planning has never been given enough attention as a distinct process, has resulted in undesirable land-use changes. Second, the process employed in the formulation and production of the Nueva Ecija Land-use Plan and Policy is examined. This is a first attempt in the Philippines to produce a provincial land-use plan and policy. It is important to analyze the plan and to determine what lessons can be learned from the experience with provincial land-use planning. The discussion brings to light some oversights that will prove useful in the process of formulating future land-use plans and policies. Third, this chapter presents an interpretation of what implications the Nueva Ecija Land-use Plan and Policy has on future changes in land-use in the basin. A GIS analysis was undertaken to compare the existing land-use cover and the proposed land-use plan. The results indicate that the plan and policy must be improved tremendously if future sustainability of agriculture is to become a reality. 48 4.1 The approach to land-use planning in the NEDA 's Development Plans There are many factors that may influence the land-use changes discussed in the preceeding chapter, but only those that relate to the planning aspect as revealed in the region's principal planning agency development plans were considered for discussion in this chapter. However, a cursory acknowledgement is due to the influence of land ownership on land conversion since it is one of the major problems in the region (Salita, 1974). The region has the largest percentage of landless tenants in the Philippines, a major factor for making it the birth place of the socialist movement in the country. Because of this, agrarian reform was initiated during the Martial Law years, where landless tenants were given a chance to become owners of the land they till. According to the report by Sly (1993), the Department of Agrarian Reform (DAR) was established and mandated to plan and program the acquisition and distribution of all agricultural lands through the Comprehensive Agrarian Reform Program (CARP). The main indicator of success of their plans is the transfer of land ownership or control to the farmer tenant. It is expected therefore that the lands transferred will remain agricultural. Unfortunately, there is now a question of whether CARP has encouraged more conversion of agricultural lands to non-agricultural losses. Among other reasons, the rate of conversion may be related to the desire of land owners to cash-in on their lands and circumvent the CARP, since a private land owner is free to use his land in most ways that he desires. Furthermore, lands classified as non-agricultural in town plans approved by H L U R B prior to the effectivity of CARP can be converted without approval from DAR. Although the law mandates that CARP awarded lands could not be converted into non-agricultural uses within the period of five years, the fact that D A R reports of illegal conversions (IDP/NE, 1994), is an indication of this problem. 49 4.1.1 NEDA's Development Plans Literature on land-use planning in the region is lacking. The only materials that will consistently reveal any form of land-use planning are the DPs of NED A, which are published by the Central Luzon Regional Development Council (RDC). With a secretariat based at the N E D A for Central Luzon, the RDC was formally organized in October 1974, and has served as the umbrella organization for coordinating, monitoring, and implementing regional and local development plans, programs and projects (RDC, 1975). .The DPs reflect the above functions, and contain the past, present and future potentials, of the resources, problems and needs of the region. The three DPs that were examined for the study were published in 1975 (first to be published), 1986, and 1992 (last to be published). Although these DPs lean more on the economic state and projection of the region, related concerns such as rapid population growth, urbanization, and environmental degradation are considered as well. Land-use is discussed in the DPs in the context of physical planning. Reviewing the DPs therefore will serve the purpose of getting an insight into the land-use planning strategies of the regional planners. However, in Central Luzon, national policies are major considerations in regional planning since this region is a major catchment area for industrial and population movements of the National Capital Region (Malaya, 1991). In terms of land-use, the DPs have attempted to show the proposed location of future urban growth centres but mainly for government decisions on large development interests. These DPs therefore provided very general guidance for provincial or municipal planning. Furthermore, the review of the DP has shown that there has been little interest in regional or provincial land-use planning, with a preference for making most decisions at the national and municipal levels. This has produced land-use plans of municipalities which have been requested, but not legally required by national agencies such as the Housing and Land-use Regulatory Board (HLURB), which up to 50 this time does not have a total compliance from the municipalities. Since the regional and provincial governments have not been involved in the program, municipal and regional or provincial land-use plans are not consistent with each other. With the government's effort to decentralize its functions, regional and provincial offices have only lately become more prominent actors in land-use planning. The Regional Perspective Development Plan of Region III (1976-2000) The first DP reviewed was the Regional Perspective Development Plan of Region III for 1976 to 2000 (RDC, 1975). The following sections are land-use related highlights of this DP: The problems in the region, including the proliferation of slums, water shortages, inadequate waste disposal, and pollution of water, were attributed to the unabated regional population increase. The high population growth, which has always been higher than the country's average, must have been a factor in the increased conversion of grasslands, forests and even wetlands into agricultural areas and the agricultural areas into settlements, as concluded in the preceding chapter. Urban growth which followed a linear pattern has been acknowledged in the DP, as increases in human settlements along the national road trunklines have been observed. This pattern was recognized to affect the people and the balance of areas in the process of economic development, and therefore, the formulation of policies to prevent the tragedies of urban sprawl has been the goal. There has been no mention of a strategy to limit the growth however, and up to the present times, this partem has remained. This explains the high rate of agricultural land conversion along major roads as concluded in the preceding chapter. There were indications that the planners were already resigned to the idea that agricultural areas will give way for urban and industrial development and that existing woodland will be 51 released for the expansion of pastures, tree farming, and other agricultural purposes. What was discouraging was that there was no indication in the plan that the planners searched for means to stop the land-use change. Even the plan for reforestation on lands of 30-65% slope came not out of land-use planning, but as a remedial measure of the worsening erosion problems. Undesirable land-use changes therefore ocurred, and are still occurring, as indicated by the data presented in the preceding chapter. Clearly, the region did not have a land-use plan and policy in 1975. However, the DP recommended the necessity to develop one, specifically, calling for the formulation of policies to prevent urban sprawl. The lack of a regional plan was attributed to the centralization of decision making in the country before the establishment of regional offices in 1972. This lack of plan therefore was, in a way another factor that paved the way for the land-use changes observed in the region up to 1975. The Medium Term Regional Development Plan ofNEDA Region 111(1987-1992) The second DP reviewed was the The Medium Term Regional Development Plan for 1987 to 1992 (RDC, 1986). Land-use-related highlights of this DP include the following: There was a decrease in agricultural production in the early 1980's which was attributed to high costs of production input and lack of rain water. The DP reported that the annual average growth of 8.31 % realized in rice production during the late 1970's, dwindled to a negative 19.4 % in the early 1980's. Although there was no link made between land-use changes and rice production, data on land-use changes presented in the preceding chapter suggest that the decrease in agricultural lands may have contributed to the decline. This was evident in the DPs report of continued conversion of prime agricultural lands and denudation of woodlands which was still attributed to population pressure and increased rate of urbanization. 52 Because of the decreased production, the DP promoted the strategy for sustained agricultural production through intensification and diversification, acknowledging the fact that there were no more additional agricultural lands available for cultivation. Moreover, this decrease in production may have convinced planners to take a stronger stand in preventing the conversion of agricultural land to industrial and urban uses, making the suggested link between decreased production and land conversion more likely. Acknowledging all the problems brought about by the expansion of settlements, the DP called for a planned development and expansion of settlement. The concern regarding the possible connection between expansion of settlements and decreased agricultural production, however, may have its roots at the national level. For example, PD 815 which prohibited the conversion of agricultural lands to urban uses was promulgated during this time. Furthermore, the Department of Agriculture (DA) initiated the re-classification of grasslands and woodlands potentially suited to agriculture, although these re-classified lands have not been very productive. The DP reports that at the time illegal conversions were occurring in the region, a sizable portion of the excess labor from the agriculture sector penetrated the region's woodlands in their quest for economic opportunities. As mentioned in Chapter 1, this problem resulted out of the construction of the Pantabangan Dam, where laborers decided to stay in and cultivated these non-agricultural areas after the dam was built. It was reported in the DP that the slash-and-burn practices and production of charcoal by the dwellers in these areas have been most destructive to the land and water quality. Thus, the government instituted the Integrated Social Forestry Program in 1987. This program was expected to remedy the problems whilst improving the economic plight of the dwellers, and may well be one reason for the recent increase in woodland areas, observed in the preceding chapter. 53 The developmental goals of the DP in terms of land-use, included an integrated and systematic agriculture, forestry, and mineral resource management, the undertaking of a continuing inventory and assessment of the region's natural resources, and the maintenance of an ecologically balanced environment. Based on these goals, a comprehensive regional land-use policy was recommended. However, the decrease in agricultural areas was the prime motivation for the formulation of a physical planning framework for the management of land-use, not only in the region but throughout the whole country. The Medium Term Regional Development Plan NEDA Region III (1993-1998) The third DP reviewed in this study was the Medium Term Regional Development Plan of Region III for 1993 tol998 (RDC, 1992). The land-use related highlights are the following: The physical planning portion of the 1992 DP was envisioned to serve as a guide for sub-regional planning. In the DPs of 1975 and 1986, there was confusion on how to subdivide the region for planning purposes. Although the watershed has been the natural region for hydrological planning, it was not applicable in terms of administration. A familiar concept has been that of a functional region which comprises separate elements, such as cities, towns and villages which depend on each other. This idea was tried in the form of Integrated Areas for Development (IAD) in the 1986 DP, where every province is an IAD. The most common difficulty in this approach as reported in the DP, arises when the built-up area of towns and cities has extended well beyond their boundaries. In order to improve and organize the development of the region, the 1992 DP calls for the whole Central Luzon region to be divided into two broad areas of development based on their physical characteristics (West Central Luzon and the East Central Luzon area). The latter area is the approximate basin boundary of the Pampanga River Basin and is planned for combined agricultural modernization and agri-business development, while at the same time enhancing access 54 to and from Northern Luzon and Metro Manila. The former area is expected to host heavy industries. The agri-industrial development strategy of the region was to guide the general direction of economic development in the region. The first component of the strategy guarantees that new industrial estates would not be encouraged in the medium term, since the existing areas could still hold the number of industries expected to locate in designated industrial areas. The second component calls for the enhancement of productivity through crop diversification and intensification. The third component ensures the adequate protection for and effective management of, the region's biological ecosystems and resources, in the attainment of overall environmental quality. The specific land-use and environmental management goal in the 1992 DP calls for a careful physical and land-use re-planning of the region, specifically for the agricultural and forested areas and the major river systems and watersheds affected by lahar. Specific objectives mentioned were a balanced and rational land-use, a significant net increase in forest cover to arrest denudation and environmental degradation, and a pollution reduction in the major river systems. The DP reports that conversion of agricultural lands to other uses has been growing at an alarming rate, although supporting figures were never supplied. Another concern was the declining forest. Despite reforestation activities, figures presented indicate the forest cover of the region to be < 20 %. It was suggested that this may have happened as a result of the region's increasing population and illegal logging, where deforestation has destroyed 7045 hectares yearly from 1987 to 1991. However, forest cover is expected to improve from 363,500 hectares in 1992 to 434,800 hectares in 1998 as the government increases its reforestation efforts. The single most destructive land-use change that was addressed in the plan was the lahar flow from the slopes of Mt. Pinatubo. Accordingly, for the next five to ten years, these destructive 55 materials will continue to cause damage to life and property. Flashfloods due to heavy siltation and clogging of rivers and waterways will also continue to threaten a wide and extensive area in the region. Unfortunately, the DP approached the problem through engineering solutions rather than the more practical approaches such as permanent relocation of affected communities. The policies and strategies in the latest DP reflect theconcern with land-use and the overall environment-development interaction, and it is anticipated that the regional and the local governments will be involved in its formulation. There are, however, obstacles in this pursuit, and although this plan has achieved some success with the Nueva Ecija Land-use plan and policy, there are problems that make these policies difficult to achieve. 4.1.2 Problems and Opportunities in Regional Land-use Planning From the review of the DPs come common problems that have sustained the land-use changes discussed in the preceding chapter. These problems are enumerated here, and as much as possible, solutions are suggested to provide for the improvement of the planning process. Unclear terms of goals Although the importance of the region for rice production has been emphasized, the regional policy on land-use has never been defined in terms of precise goals or targets. If these were defined in terms of the hectares of rice fields that are necessary to feed the population of the basin or other targets, then there will be a specific gauge for assessment of land-use changes. Lack of data and information Most of the public debate over land-use policies has taken place without the benefit of available facts concerning the patterns and trends in land-use. A simple policy prohibiting the 56 conversion of the best grades of agricultural land will not in general be appropriate since in the absence of empirical analysis, one cannot determine the merits of the argument that agricultural areas are being converted to settlements in an unsustainable manner. Any land-use plan based on limited or inadequate information is lopsided and would be bound to fail or become plans that may never be enforced. Although social, economic and political data and information are available to planners in the region, those specifically related to land-use planning are lacking. For example, no regional system of documenting and monitoring land-use changes on a regular basis exists. Because land-use data are incomplete and incomparable, it is difficult to try to answer allocation of the various classes of agricultural land among different uses, particularly agricultural uses or how much of the various classes of land are being permanently and irreversibly converted to other uses each year. The empirical results obtained in my study may form a part of the statistical information base in the region. The hope is that of strengthening data and information to serve as a necessary tool for decision-making by the private and government sectors. The establishment of a regional level GIS at the NEDA-CL , although designed primarily for the survey of lahar-covered areas resulting from Mt. Pinatubo's eruption, may be a good starting point for a land-use inventory, barangay updating, and land-use modeling programs. Lack of a dissenting voice In developed countries, many conflicts over the use of land becomes a battle between the interests of developers and environmentalists, with the planners stuck in the middle trying to resolve the differences between the two. In the Philippines, it is only quite recently that active environmental organizations have emerged, and their role to pressure the government, to educate the public, or to stimulate local debate, about the environmental consequences of land-use changes, 57 has not been visible. Without the representation of the environmentalists in the land-use debate, many land-use decisions in the region become unopposed and predictably in favor of developers. Therefore, pressures for land development in the region have predominantly been a response to changing market conditions and political encouragement at all political levels. For example, even barangays welcome the conversion of rice fields, swamps or grasslands to the more economically-rewarding industrial or residential subdivisions. Lack of appropriate legislation The Philippines is experiencing very rapid urban growth, but still has only an embryonic government physical planning system. For example, the Guidelines of the Provincial Physical Framework Plan ( D I L G , 1992) were only released in 1992. Since such legislation was absent in the past, even concerns for the rapid land-use changes regularly addressed in the DPs were not enough to keep agricultural lands from disappearing. In the case of provincial planners, the lack of legislation gives them no authority over municipal plans. Although there is implied power for the provincial government, this responsibility is not clear since the national government has always been dealing directly with the municipalities rather than with the province. Lack of co-ordination It was evident in the past DPs that the absence of effective co-ordination in the administration of development efforts in the past has been an obstacle to efficient planning. The 1992 D P however endorsed the development of closer and workable relationships between the regional and local development councils and legislators in the need for careful physical and land-use re-planning of the region. Specifically, it called for the linking of the R D C with other land-use planning agencies. 58 It was recognized that although planning functions have to be centralized to ensure a unified effort and prevent various inconsistencies, a degree of decentralization is needed to bring decision-making structures close to the people and ensure effective implementation. The 1992 DP mentioned that this form of co-ordination has already been employed in the case of general development concerns, through the formulation of the plan following a two-way process: the top-down and the bottom-up approaches. For the top-down process, the plan was formulated in consonance with the national development framework. To serve as guide for sub-regional planning, a regional development framework was formulated and issued to all regional line agencies and local government units. While the regional plan was made consistent with the draft national plan, it also incorporated inputs from the provinces, the cities, the non-governmental organizations and the private sector. It is through this direction of regional planning that the next section on the land-use plan and policy of Nueva Ecija, was conceived. 4.2 The Nueva Ecija Land-use Plan and Policy: A case study of Land-use Planning Process The Nueva Ecija Land-use Plan and Policy Project, referred from this point on as the 'project," was hailed as the first in the Philippines (IDP/NE, 1994). In perspective however, the province of Palawan had a Physical Framework Plan (PFP) before Nueva Ecija, but it was a joint initiative of the national government and the European Economic Gommunity, where, after its formulation, Congress helped to transform the Palawan PFP into a Republic Act (Serote, 1994: Personal Communication). In April 1994, a seminar workshop on municipal land-use planning in Palawan was conducted. The procedure for the Nueva Ecija Land-use Plan was different and more difficult since a provincial plan the municipalities can use as a pattern for their own area is lacking. It is important 59 to analyze the plan and to determine what lessons can be learned from this experience with provincial regional planning. The 'project" in a sense is the first of its kind since the provincial level planning evolved from the municipal level. Nueva Ecija therefore, which boasts of pioneering the participatory approach in the country (Umipig, 1994: personal communication) has made the first truly provincial land-use plan. 4.2.1 Legal Background of the Project3 The legal framework that paved the way for the Nueva Ecija land-use plan began as early as 1990 when Administrative Order No. 1 was issued. This provided a set of rules and regulations governing conversion of private agricultural lands to non-agricultural uses. Executive Order 129 and Republic Act 6657 (the Comprehensive Agrarian Reform Law), empowered the D A R to approve or disapprove this land conversion. Republic Act 7160 (the Local Government Code) of 1991 and the June 1993 Memorandum Circular No. 54, empowered the municipalities to reclassify agricultural lands to non-agricultural uses following a maximum allowable conversion rate of 15 % for highly urbanized and independent component cities, 10% for component cities and first to third class municipalities, and 5% for fourth to sixth class municipalities. The Regional Physical Framework Plan as approved by the RDC was to be used as a basis for decision-making. But in all cases however, conversion required a certification from the DENR that the conversion is ecologically sound. In 1992 the DILG (Circulars 92-05 and 92-06) provided the guidelines for the formulation of the Provincial Physical Framework Plan (PPFP), a framework followed by the province of Nueva Ecija. The PPFP is a document that translates provincial policies and objectives into a general land use plan, indicating the manner in which land shall be put to use in the next ten years. The inconsistencies of land-use plans of the different 3 References for this section came from description of the different laws in the Nueva Ecija Land-use Plan and Policy (Draft), and mimeographed articles distributed during the workshops. 60 levels of government, as pointed out by the review of the DPs, are therefore addressed by the PPFP. It is in this legal framework that the Nueva Ecija Land-use Plan and Policy was envisioned. 4.2.2 The Process The project procedure involved three workshops participated in by the Municipal Planning and Development Coordinators (MPDCs), the Provincial Land-use Committee (PLUC) which is composed of representatives from different line agencies of the provincial government, the Provincial Planning and Development Office (PPDO), and the Integrated Development Project of Nueva Ecija (IDP/NE). The project secretariat had its quarters at the IDP/NE offices. The introductory workshop involved informing the MPDCs of the project and their responsibility of contributing a land-use plan of their own municipalities. The IDP/NE cartographers produced basic land-use maps at the 1:50,000 scale based on 1990 N A M R I A Topographic maps and the 1988 Land-use map of Nueva Ecija from BSWM. During the consultation, each MPDC counterchecked the prepared maps. The project staff visited controversial sites for inspection before the maps were modified. It is at this point in the process that the municipal boundaries, as will be explained later, became a problem. A present land-use map for each municipality in the province was produced in the first workshop. The second workshop involved the MPDCs working on the modified land-use map, indicating where land-use changes can be made, bearing in mind the maximum allowable expansion of settlements on agricultural areas for their own municipality. In this step in the procedure, the linear type of development (human settlements develop along the national road trunklines) was considered. Part of the workshop involved the presentation of agency plans related to land-use by each of the members of the PLUC, which was to be considered by the MPDCs in their activity. Another part of the workshop involved a discussion on land-use policy for the 61 province where organizers divided the participants into sub-groups. Through consultation of the staff and the individual MPDC of each municipality, a proposed land-use map was produced for each municipality. The third and final meeting of all the participants in the project was the presentation of the draft provincial land-use plan and policy. Invited to comment on the draft plan were representatives from DAR, the N E D A - C L and the UP-SURP. Mr. Tiburcio Morales, Jr. from D A R explained the rationale of the project. He said that illegal conversions of prime agricultural lands are about ten times that of the approved conversions and that people do not report illegal conversions. He added that with a land-use plan and policy, the Local Government Units (municipalities) can convert lands without the need for debates and arguments. Moreover, he pointed to the need of a land-use plan. He cited the case of the Calabarzon as an example, where, due to the absence of a landruse plan, owners of agricultural lands have been enticed by rosy offers of developers resulting in the conversion of agricultural lands to golf courses. The Nueva Ecija land-use plan was to be submitted to N E D A - C L followed by a review and evaluation by H L U R B as mandated by Executive Order No. 648. Although a draft was created, no schedule for implementation of the plan was indicated. 4.2.2 Problems associated with the process Several problems occurred in the process of developing the provincial land-use plan. Some of these are presented in the following section. Boundary disputes Boundary disputes occured not only among municipalities in the same province, but among municipalities of different provinces, indicating that problem exists, at all levels of administrative 62 boundaries. Provincial boundaries have come into contests, bringing border municipalities into the conflict. A case in point is the disputed boundary of the provinces of Aurora and Nueva Ecija, where the disputed area is located in the municipality of Pantabangan. Some boundary disputes that occurred were due to cartographic oversight. For example, the municipality of Quezon protested the loss of an entire barangay to the municipality of Sto. Domingo. Boundary disputes also extend into the differences in reported municipal areas, or in the boundaries of the barangays. For example, the MPDC from municipality of Talavera complained of a reported shrinkage in area, while MPDCs representing municipalities with bigger reported areas than those in their documents did not object. Boundary problems are real and troublesome, especially with the passing of DILG Circular 92 in February 1992, otherwise known as the Internal Resource Allocation of L G U . This allocation is based on the population and land area, and with this allocation, every municipality tries hard to have a bigger land area and a higher population. This is a very strong incentive for the MPDCs to be non-committal on their municipal boundaries, as reported in the plan. I digitized the cadastral maps of the municipalities from the Bureau of Land Management (BLM) of the DENR, the authority in land area survey, and it became apparent that most of the municipal boundaries used for the provinces and boundaries used for the barangays based on the B L M maps, were very different from those used in the plan. Since boundaries on the topographic maps are not authoritative, the cadastral maps in the B L M should have been used instead. Determination of an authoritative definition of the boundaries and the consequent areas should be dealt with as soon as possible. As long as it is not fixed, disputes will surely persist, and land-use plans would just remain as exercises rather than legal documents. 63 Problem of land reclassification and conversion The proposal to simply use the maximum allowable area to be converted in each municipality is very far from being creative and realistic. Different municipalities have different infrastructures, different degrees of development, and thus should have different conversion rates. However, the MPDCs have made use of the 5% maximum expansion on agricultural lands. The practice followed was to multiply the agricultural areas by 5% and make the resulting area the extent that the municipality can reclassify from the agricultural land. However, a problem of spatial distribution of these conversions emerged. There was a question of where these agricultural lands should come from. It was suggested that there should be a proportional distribution of the converted areas, although distribution based on trend analysis was a more logical approach. The allocation of land per municipality using percentages of the L G C provision is very arbitrary. Limited expansion would mean limited development in a municipality, since a larger income usually results from taxes on urban expansion. Allocation based on needs of each municipality would have been better. Factors such as projected population and economic forecasts, investments, and degree of development of the municipality should have been considered in the process. If the provincial development concept is to limit urban areas, the plan should have strategies to encourage people to settle in designated areas. Therefore, some municipalities should be given the allocation that they need regardless of the 5% conversion required. In Nueva Ecija, it has been suggested that urban development should be diverted to the foothills of the Sierra Madre rather than allowing urban development to eat up agricultural land (Mercado, 1994: Personal Communication). 64 A question of authority In the workshop, some MPDCs refused to work on the maps produced by the cartographic team and wanted to work on their own maps. Their reasons go back to the problem of disputed boundaries. These participants said that their hesitation was due to the fact that as municipal planners, they are limited as to what they wanted to do and need to consult with the mayors before committing to any plan. The organizers were able to persuade them to work when they were assured that this was just an exercise, and the results would not be binding and the draft would not become a legal document. This shows that the autonomy of planning officers is very limited, as civil servants are usually appointed to the position by the elected representatives who have the final say on most planning issues. 4.3 The Nueva Ecija Land-use Plan: Implications for the Future of Sustainable Agriculture in the basin The report on Nueva Ecija Land-use Plan and Policy, consisting of two volumes, was drafted and commented upon by the N E D A Director for Central Luzon, as well as by the invited professors of the University of the Philippines- School of Urban and Regional Planning, at the last meeting of the participants. This section makes a report and a critique of the land-use changes effected by the plan, concluding that the land-use plan was merely an exercise in the selection of a percentage for land conversion, and far from being a product of a creative approach that considers practicality and implementability. 65 4.3.1 A report and critique of the land-use plan The existing (see Figure 3-7) and the proposed (Figure 4-1) land-use maps produced by the project, both at the 1:50,000 scale and encompassing the Nueva Ecija Area, were digitized and analyzed through the use of Terrasoft GIS software. Land-use changes in the municipalities Although the intentions of the MPDCs were all in consonance with the allowable land conversion in their own municipalities, factors that affect the use of land for certain purposes have not been considered. In the proposed plan, Cabanatuan City, being a highly urbanized municipality, had the highest allowable conversion rate of 15 %. San Jose City followed with 10%, half of which was the allowable conversion of the agricultural lands to settlements, and the other half for the resettlement of Mt. Pinatubo victims in grassland areas. Although a majority of the MPDCs took the maximum allowable reclassification from agriculture settlements, some exemptions were worth noting: The municipality of Carranglan opted not to have decreases in the agricultural land base, but the 5% expansion of settlements would come from a portion of grasslands and woodlands classified by the DENR as having a slope which could be inhabited. However, the likelihood of settlements expanding into these areas when they might be far from the roads or the urban communities, has not been considered. The most common system is to use agricultural lands for settlement extension and expand agriculture into the grasslands. This is exactly what might result in the municipalities of Cabiao, Sta. Rosa, and Zaragoza, if the MPDCs plans are put in place. However, in this approach, the suitability of grasslands for the traditional rice farming practices was not addressed either. The case of the municipality of Laur presents another approach. Since the planner did not want to 66 Figure 4-1. Land-use evaluation of the Nueva Ecija Area from 1:50,000 Proposed Land-use Map (IDP/NE, 1994) Nueva Ecija Area Proposed Land-use Map • • - • ..*r n . LAND-USE CLASSIFICATIONS • IRRIGATED RICEFIELDS • RAIN FED RICEFIELDS • SETTLEMENTS • WOODLANDS • GRASSLANDS • SUGARCANE FIELDS • VEGETABLE FIELDS • WETLANDS 1 0 0: 1 0 2 0 TO Km 67 decrease the agricultural area of the municipality by converting it to settlements; any increase in settlements was taken from portions of the grassland. The complexity of reclassifying land is exemplified by the proposal for the municipality of Munoz. An almost equal amount of land from its river-wash and grassland would compensate for the agricultural land that goes into settlements. Here again, although the required total area for reclassification was satisfied, the problem of reclaiming the riverwash areas for agricultural purposes when such areas are prone to flooding and with dire environmental consequences, was not considered. The same problem of a plan that is not environmentally sensitive is that proposed for Pantabangan. In this case, the relatively small agricultural area cannot be reclassified for settlement purposes without greatly affecting food production, therefore, the plan was to take the woodlands for the increased built-up areas. Similarly, in the case of the small municipality of San Isidro the plan was to keep the agricultural areas intact and reclassifying barelands for settlements. In their rush to satisfy the allowable total area for reclassification, the MPDCs were overshadowed by the percentages rather than by practicality and consideration of important factors. This resulted in a land-use plan that satisfies the quantitative requirements but is deficient in practicality and realism. The overall land-use change in the province Results of overlay analysis conducted on the raster layers of the two maps are summarized in Table 4.1. It can be observed that the expansion of settlement sites decreased both the irrigated and the rain-fed rice fields as well as resulting in a small decrease in grasslands. Although the land-use plan was envisioned to protect agricultural lands from conversion to settlements, the reality is the contrary (see Figure 4-2). This is evident in the comparison made between conversion rates of agricultural lands from 1988-1993 (results from the preceding chapter) and that 68 from 1993 and the proposed plan. With the proposed land-use plan, 1.5 % of the irrigated rice fields will be converted to settlements, while only 1.3 % was converted from 1988 to 1993. Similarly, with the proposed land-use plan 0.9 % of the rain-fed rice fields will be converted to settlements, while only 0.6 % was converted from 1988 to 1993. Table 4.1 Comparison of land-use in the Nueva Ecija Area when the plan is carried out Land-use Classifications 1993 Land-use Proposed Land-use (%) (%) Ricefields Irrigated 26.5 25.1 Rainfed 16.2 15.3 Settlements 4.6 7.6 Woodlands 27.2 27.0 Pasture/meadows 22.3 21.8 Sugarcane fields 0.1 0.1 Vegetable areas 1.9 1.9 Wetlands 1.2 1.2 Total 100 100 1.5 % 0.4%' 0.2 % 0.1% Settlement 0.9 % Rain-fed + 30% - 0 9 % Giassland Woodland -0.5% 0.1% -0 2% Figure 4-2. Resulting land-use dynamics from 1993 if the proposed Nueva Ecija land-use plan is carried out. Arrows indicate the net direction and value of change from one classification to another. All percentages are in terms of the whole area being compared. 69 4.3.2 Potential problems in implementation Aside from the real problem that the plan might not be able to preserve agricultural lands as the above case suggests, there is also the anticipated problem of implementation. There were doubts among the participants that the policies may be compromised, citing a common example. It was alleged that an irrigated rice field along a major road was covered with gravel and sand when it was almost ready to be harvested. Large buildings were constructed on the site to become the largest cold storage plant in the province. It was a common perception that the DAR lost the case due to the fact that the owner was a high-ranking official of the province. The following are some of the factors that might influence whether or not the plan would have full implementation. Provincial- municipal conflicts In order to implement the proposed provincial land-use plan and policy, the province is relying primarily on the action of the different municipalities to designate and protect agricultural land in their official plan and other land-use decisions. The autonomy of the municipalities presents a problem in the implementation of the provincial plan. Although the province has power over the municipalities (due to the transfer of this power to approve land-use plans from the HLURB to the province), there has been no indication from the meetings that the province would ever use this power. It seems likely then that the province would get the same response from the municipalities as the HLURB got out of similar requests from the municipalities. The provincial government may be criticized in its decision to rely solely on guidelines for municipal action rather than direct provincial legislation to protect agricultural land. There is a perceived indication that local authorities do not always adopt the appropriate policies for dealing with local problems. This is a concern because the municipal government is very much in power in land-use allocation through its control of the subdivision approval process. At the moment, the power to enact land-use plans rests with the municipalities and not with the province. 70 Between the national government and municipalities, there should be consultation with the provincial government. Policies should be developed to guide the municipalities in the province in preparing their land use plans, but the province's role in coordinating and directing the activities should be clearly stated. The Nueva Ecija land-use plan and policy should be improved and made a legal document in order for it to be implemented. But the fact that some of the Nueva Ecija municipalities have ready-made plans which provincial government has no means of checking, least of all approving or disapproving according to the provincial policy, is of utmost concern. Policies other than land-use control The land-use policy proposal is entirely based on traditional direct regulation of land-use through planning controls which restrict land-use through the physical framework. Other provincial policies which may often have a more important effect on land-use in the province should not be neglected. One obvious example is the provincial responsibility in the prioritization of infrastructure facilities and sites of development. Almost any policy which has an important impact on the economy will, of course, influence the location of economic activity and land-use to some extent. Therefore, it must be realized that in the formulation of future land-use plans, the effects of these policies must not be ignored. It might be through these provisions that the province may yet be able to get what it wants with regard municipalities to following the plan. Limited environmental concerns Two approaches have been suggested by the PPFP to address the issue of sustainable development in the land-use plan. These are identifying the areas for conservation and preservation of natural resources and the segregation of environmentally critical areas (ECA). The Nueva Ecija land-use plan addressed the conservation of agricultural areas but not the segregation of ECA. For example, there is heavy reliance of maps from B S W M (agriculture), although the areas intended to be protected are mostly in the public domain and administered by the DENR. To improve the plan, 71 maps from both the BSWM and the DENR should be used to account for a more complete coverage of the other land-uses in the area. While wetlands, grasslands and woodlands have been indirectly addressed through their contribution to agricultural expansion, the influence of land on water resources has never been discussed. 4.4 Toward a land-use plan that supports agricultural sustainability The review of NEDA's development plans suggested that there was a lack of attention to land-use planning such that plans did nothing to discourage the undesirable land-use changes that have taken place in the basin. There are indications however, that this is changing, partly motivated by the critical situation of agricultural production and land conversion in the region. It is likely that as more land-use planning exercises are undertaken by all levels of government, the solutions to the problem would be available before there is irreversible damage to the land base. A final finding on the success the Nueva Ecija Land-use Plan cannot be made at this point, and the question of whether the plan will work and achieve its aims will be for the future to tell. The proposal was still a draft when the present study was conducted, but hopefully, there will be improvements to the plan; also, additional analysis would refine it. However, if the draft were to be accepted at face value, possible problems of further loss of agricultural lands to settlements as well as the loss of ecologically-important land-uses such as the wetlands and grasslands would inevitably occur. The Nueva Ecija Land-use Plan and Policy provided a considerable insight into the problems, challenges and arrangements that must be made in order to work out a feasible land-use plan. If the land-use plan and policy is to be geared towards the attainment of sustainable agriculture, then the effect of land-use on water should be taken into consideration. This component was left out in the plan, but is the topic of the next chapter. Chapter 5. W A T E R QUALITY ASSESSMENT OF T H E P A M P A N G A R I V E R AND ITS TRIBUTARIES In order to assess the impact of land-use on water quality, or even determine the effects of its interaction on the sustainability of agriculture in the Pampanga river basin, the condition of water quality in the river and its tributaries must first be established. This chapter investigates the quality of the mainstem and tributaries of the Pampanga river, and their characteristics that will reveal both natural and contaminated water quality conditions. Since a review of the literature revealed a lack of both spatial and temporal water quality data, and since it was often difficult to provide basin-wide perspectives, this assessment relied heavily on the data gathered from monitoring during this investigation. Figure 5-1 portrays the geographical position of the water quality sampling stations used in the study as well as their catchment areas. The data from these water quality sampling stations were first grouped into two categories- the mainstem and the tributary groups, and statistical analysis and interpretation were carried out separately for both categories. Wherever possible however, a discussion on how the tributary streams are affecting the mainstem is provided. This chapter examines the water quality conditions by discussing related water quality parameters in terms of their spatial and temporal variation. Where possible, results have been compared with historic data to show longer temporal changes and trends, and with recent water quality data in other parts of the country to give it a national perspective. Although in explaining the differences among the stations in terms of water quality, some of the effect of land-use on the water quality are mentioned, no effort was made to exhaustively discuss the relationship, since this is done in subsequent chapters. Figure 5-1. Location of sampling stations and catchment boundaries in the Pampanga River Basin m Catchment Boundaries 0 1 0 2 0 TO Km 74 5.1 Discharge data for the Pampanga river system and the three flow periods Sampling for water quality was started in the first week of November 1993 and ended in the last week of July 1994. It can be clearly seen in Figure 5-2 that the sampling period follows a reverse hydrograph in that it starts at the falling limb of the 1993 hydrographs and ends with the rising limb of the 1994 hydrographs. When the discharge data of these stations were averaged per month and then statistically analyzed, three significantly different (p<0.05) groups emerged: The falling limb of the high flow period which included the months of November and December 1993 (falling limb period); the low flow period which included the dry season months of January to June 1994; and the rising limb of the high flow period which was the last month of sampling (rising limb period). Although as mentioned in Chapter 1, there are two distinct seasons in the basin- the dry and the rainy seasons, use of the three periods provided a more meaningful and logical discussion. The importance of discharge measurements and analysis is crucial in the analysis of water quality parameters, as the ability of the volume to dilute or intensify substances in water greatly influences their concentration. In fact, discharge is significantly (p<0.05) correlated to the majority of water quality parameters measured in the study. In the interpretation of the dynamics of these substances, the influence of discharge was always taken into consideration to make a sound conclusion. It is therefore necessary to assess the spatial and temporal variability of discharge measurements, even before discussing the water quality parameters themselves. As can be observed in Figure 5-3, the rising limb period shows a great variability in discharge measurements as compared to the other periods. This variability, which may be attributed to the uneven rainfall pattern in the basin during the start of the rainy season, is important in the interpretation of water quality results, particularly in comparing values among the three flow periods. Figure 5-4 reveals that along the mainstem stations, the general trend is for the 77 river to increase in discharge as it travels from its headwaters to its mouth. At certain portions of the graphs however, are observable decreases from upstream to downstream stations. A case in point is the decrease in discharge from the upstream Station 8 to the downstream Station 11 during the falling limb and low flow periods^ notwithstanding the major contribution of the tributary Station 10. The diversion of the river for agricultural purposes by the Atate dam at Station 8 is the reason for the observed decrease. Only when the rainy season has arrived does an increase in discharge register, owing to the fact that water requirement for rice production at this period is adequately supplied by rainfall, and the water is again released back to the river. Discharge decreases from the upstream to the downstream stations during the start of the rainy season may also be explained by the presence of natural recharge sites, and among the major ones are the San Antonio swamp between Stations 28 and 44, and the Candaba swamp between Stations 53 and 56. The swamps which are still saturated during the falling limb period cause the increase in discharge from the headwaters to the mouth as tributaries add to the flow, however during the beginning of the rainy season, the swamps collect rainfall to recharge the groundwater, thus the decrease in discharge. The very low discharge values of the tributaries in the first two periods can be attributed to the natural drying-up of the streams, as well as to the increase in consumptive use for farming purposes. 5 .3 Water quality of the Pampanga river and its tributaries 5.3.1 Temperature and Dissolved Oxygen Figure 5 -5 illustrates the variability of water temperature, while Figure 5-6 shows the fluctuations in mean temperature, along the Pampanga river. For the mainstem stations there were no significant differences (p<0.05) among the stations in the high flow periods (both falling and 2 3 2 CD a i » ** > c , = II .E a-o o-"5 • 5 £ 3 ** (J O) 3 C «? IO « O) E a> to iS C 3 11 iT II w SH 0 o i f 1 § o Q. (0 O T3 p i i JZ = cn co • • 8 co 2 1 5 | 2 5 &5 § £ S i — 0) S > co ' C CO co cn >. s IQ Q. to E £ a! 3 CD iZ o. *' °l 5 5 5 o o < < D O <oo O O o <-D-O T3 O •c a) 0 . o 2a E CD C co co _1_ N—• <a—o <-a—o <a—© <-o—o <D-0] <—D—O <-a-o <-a—© <-o—o < a o <—o—© o <—TJ-0 <-a—© < — D - © <-D-0 <-o© o CM in CO 8 IT) CM O CM T3 O ! l o —' U_ D) II <-Q © < Q© < - r > © <co <-oo <-o© <to <H> <n> < o-© <-a-o <x> •CD snjS|30 3 3 j 6 a a Sn;S|93 33J63Q H— I— I— I — 4 — I— I— I— r -^ ( O C O C O C O C O C M C M C N C M C M 79 rising limbs), while significant differences (p<0.05) existed during the low flow period, where the trend is generally towards increased temperature close to the mouth of the river. This trend may be attributed to the effects of altitude and tides. Headwaters which are usually on higher ground tend to be colder, while stations near the river's mouth, which are subjected to sea water intrusion, tend to be warmer. For the tributaries, significant differences (p<0.05) existed among the stations in the first two periods, and there was greater variability of temperature among the stations in the low flow period, again indicating the influence of the volume of water present in the river on its temperature. This influence of volume on temperature is supported by the statistically significant (p<0.05) negative correlation between temperature and discharge measurements. The non-significant differences (p<0.05) for the rising limb period may be explained by the fact that temperatures in the rainy season are less variable due to the modifying influence of rainwater on temperature. In terms of spatial variations, when tributary stations were arranged in increasing temperature values, some stations had consistent positions in the distribution, in all three periods. For example, Stations 4 and 7 were always on the lower end, while Stations 27, 30, 31, 37, 42, and 43 were always on the opposite end of the range. The consistently low value of the former two stations may be attributed to their higher altitude, and to their predominantly forested watersheds. For the latter group of stations, the high temperature for Station 27 is attributable to its location which is at the spillway of the Penaranda diversion dam. In most cases, the dam releases a very limited amount of water since most of the water is diverted to the irrigated rice fields. Stations 30, 31 and 37 all belong to the drier northwestern portion of the watershed where rainfall is lower, thus the expected lower discharges, and consequently high temperatures. Stations 42 and 43 are found in lahar-covered areas where the very low volume of surface water (as the water usually runs under the 80 coarse material) works with the direct heat from the sun (as there is no extensive vegetation cover), to elevate the water temperature. Although air temperatures were not recorded, it was observed during sampling that the temperatures of the tributary streams were relatively lower during cooler days, and higher during the warmer days. However, this relationship between air and stream temperatures was not clearly observed with the mainstem stations, indicating that the effect of air temperature on stream temperature is limited to the shallow tributaries. The data on temperature do not allow for the determination for abrupt increases of temperature that might indicate pollution from industry. Since the temperatures were taken once during a sampling period at the station, the hourly, diurnal or daily fluctuations cannot be determined. However, considering that the temperature criterion used in the Philippines for Class C waters by theNPCC in 1978 (Alcances et al 1983), which only requires that there are no sudden changes greater than 3 °C beyond natural minimum and maximum temperatures, it can be concluded that the ranges in temperature registered by all stations do not exceed the standard. The absence of big industries which might have used large volumes of water for cooling purposes along the streams and near sampling stations makes this argument even more logical. Figure 5-7 illustrates the variability of DO concentrations, while Figure 5-8 shows the fluctuation of mean DO concentrations and the % saturation of oxygen in the Pampanga river and its tributaries. The latter parameter was introduced to correct for any temperature effects on solubility, allowing pollutants that consume oxygen to be determined. The variability of DO concentrations follows the variability in temperature indicating the influence of temperature on DO concentration. This influence is supported by the significant (P<0.05) but negative correlation between the two parameters. In the mainstem stations, no significant (P<0.05) differences were found between the means of the stations in the first two %1 uojiejines % <B ? R UOjJBjnjBS % uoj)ejn)es % o g o g p •r- Jo to ^ CN o 8 o g g g «— co co CN o T3 O CU D_ 3 o u_ o < — D O (i/Boi) oa (I/6UI) oa (I/BUJ) oa 82 seasons. However, during the start of the rainy season, the three stations nearest to the mouth had DO concentrations that were significantly (p<0.05) lower, in spite of the observation that their temperatures were not different from those registered by other stations which were nearer to the headwaters. The above observations may indicate an increase in pollution load which occurs during the beginning of the rainy season when the wastes that accumulate on the land in the dry season are flushed into the waterways. Oxygen may be used by the microorganisms in water as they utilize the nutrients from the wastes, thereby causing the decreased concentration. This explanation is supported by the observation that the DO concentrations as well as the % saturation of dissolved oxygen in water during the rising limb period were always lower than those in the other periods. Another factor that may have caused the decreased DO concentration is the presence of chlorides. It is recognized that the solubility of oxygen in water decreases with increasing chloride concentration (APHA, 1985). The chlorides may have come from the diverse land-uses in the different catchments, but sea water intrusion may be a more reasonable source of chlorides, especially since the three stations with low DO values are the stations affected by the tides. In the case of the tributaries, significant (p<0.05) differences in DO concentrations in the tributary streams were registered in all three periods. When the tributary stations were arranged according to DO concentration values, the resulting distribution followed that of water temperature as explained in the beginning of this section. The factors that influenced temperature may be the same factors that influence the DO concentration. The very low DO values for Stations 13 and 14 during the rising limb period also indicate a possible pollution in the streams. The catchments of these stations are within the densely populated Cabanatuan City, which suggests that built-up areas affect DO concentrations in streams. 83 Since 1962, there were only isolated occurrences of DO values decreasing below the N P C C standard on DO for Class C waters, which is 5 mg/1. These occasional decreases in DO concentration, occurring in the present investigation, would indicate sporadic inputs of organic substances that consume oxygen, and/or the abrupt changes in chloride content of the stream water due to sea water intrusion. Although results in general would indicate only very few patches of polluted streams, it must be borne in mind that DO measurements were all made during daylight hours; also the values do not reflect diurnal variation when DO is utilized for respiratory activity and there is no photosynthesis during night time (Jeffries and Mills, 1990). 5.3.2 The buffering capacity of the Pampanga river system: the case of pH and alkalinity Figure 5-9 illustrates the variability in pH and Figure 5-10 shows the changes in pH in water at the study stations. The Pampanga river is very homogeneous in terms of pH, as revealed by non-significant differences (p<0.05) among the different stations in the first two flow periods. In the case of the tributaries, significant differences (p<0.05) were registered in the two high flow periods only. This indicates that the river water in all the stations was uniform and that there was no contamination of the water from factors that might have changed the pH. It must be borne in mind that the uniformity of the pH at low flow is likely attributable to the large contribution that groundwater makes to the river flow. At high flows, there are indications that factors causing the relatively uniform pH to change are present, since some pH values increase while others are decreasing. When stations were arranged according to pH values, it was observed that some stations are consistently in the upper end or on the lower end of the range. Stations 13 and 14, both with watersheds in the city of Cabanatuan are on the low pH end, as are Stations 50 and 51, which have both predominantly agricultural watersheds. On the upper end are Stations 10, 32 and 37. Station 10 is a predominantly grassland watershed, while the other two have mixed w c o « 3 <-» 0 3 U. ci • 2 3 01 E tn > (A 5 n O) c co a . E co Q. 0) > <n o <a-o <r>© 3 DO <-TJ~ " ~<a> ^ I f <TJO 5 <-rx> co co I fc co r-s)jun Hd < • — O < r O O < < D D - 0 0 co r~-s)jun Hd oo r-s)|un Hd i 85 agricultural and grassland watersheds. It is not clear why the differences in these stations occurs, but a possible explanation is that pollution is affecting pH values. Figure 5-11 presents a temporal comparison of pH in selected stations along the Pampanga river and its tributaries from published results. It is evident that there is a decreasing trend in the pH values from 1962 to the present. Although statistical comparisons were not possible because of the fragmentary nature of the published data, in general, the average pH of streams decreased over time. This suggests a possible pollution in the streams, over time, but the resulting values were still within the NEPC permissible range for Glass C waters, which is between 6.5 to 8.5. When the values from the present study were compared with values collected by the DPWH from 1986 to 1992 (Figure 5-12), it can be observed that the pH range for some stations is between 7 and 8. These values are the best for supporting and rearing of fish, and therefore indicate good stream water pH (Alcances et al, 1983). However, it can be pointed out that between 1991 and 1992 (1991 and 1992 graphs of Figure 5-12), the pH values were consistently lower (between 6 and 7). This is also evident in the high flow period values in the study. The sporadic eruption of Mount Pinatubo during the 1991-1992 years as well as the secondary eruption during the rising limb period of the present study may have caused the observed decreases in the pH of the streams. Since those eruptions consisted of blanket ashfalls throughout the basin, a lot of the volcanic ash might have contributed to acidification. Based on the results of leaching studies on the Mt. Pinatubo volcanic ash conducted by Imai et al (1993), a considerable amount of sulphates and chlorides from the ashes that enveloped much of the basin, might have produced considerable quantities of sulphuric and hydrochloric acids. These, and other acids might have caused the drop in pH. The pH, however, quickly recovered to normal levels. Figure 5-11. Comparison of pH in selected stations along the Pampanga river and its tributaries in four different periods 10 8 UPRP (1962-1973) < > < > 1 f < > < • r — r i r i r i c r-[ c •• O Maximum • Minimum Liongson (1976) ODry • Wet ? Q 0 ° • D 10 9 8 7 • 6 5 DPWH (1986-1992) 8 S a JL H 1 1- H —I-oDry • Wet 8 1 w 9 9 -i 1—-+-10 9 8 7 • 6 This Study (1993-1994) 4 O Falling Limb • Dry Season A Rising Limb 1 1 ! 1 1 1 1 1 1 1 1 1 1 1 | 1 1 4 6 7 8 10 11 17 18 19 21 27 28 33 37 39 44 Headwaters stations Mouth eo CL O E p to CD •c TO 3 •c w T3 c TO CD > TO CO c TO Q. E TO D. cu o o o> 8 cd <CH© <D O O < Q-© < O O a <o—© <•—o < D O < D « H—•—I— o o o o o o S)iun Hd sjmn Hd X CL c co •c oi I m 3 co co X 2 2<—O—0 o • < < D - O <—• o <—o—o < -CH© < — • O o < - n © <-D O <Q—0 <-• < <DO <•© < - D — © <—D-O <-DO < E « <—D © <-D- © < • 1 r-8 0> o o s)jun Hd 8 ui o o o o o o o o o o o o oo o o o o oo o> o> co cd r->-' coco iriri <--D—© <•—© <—•—© <-o © <-D C < D © <-Ch© <D© <CH© <D © O © c g O) CO r -co co co sjjun n d 8 8 8 00 <D s j iun Hd 8 ui c o (0 00 CM CD CD *• TO „ T 3 O TO * " CD ^ X 88 One reason for the quick recovery is that occurrence of the acid rain was only temporary and sporadic. Blong (1984) described this sporadic occurrence from a review of volcanic eruptions including that of Mount Mayon (another volcano in the island of Luzon, Philippines). Accordingly, acid rain from volcanoes are dependent not only on the drift of fumes but also on the presence of the atmospheric conditions necessary to produce precipitation at the time when acid-laden clouds are passing overhead. Research has shown that rainwater samples from a single heavy rainfall were less acidic than from cumulative samples of lighter rainfalls, indicating that the first portion of a rainfall absorbs most of the pollutants from the air. Another reason for the quick recovery is the naturally high alkalinity and hardness of water in the Pampanga river system. Figures 5-13 and 5-14 show the range of values and variability of total alkalinity and total hardness of the rivers and streams, respectively. The very high values of both alkalinity and hardness, when compared with the desirable levels of >40 mg CaCOs/l and >20 mg CaCOj/l, respectively, indicate the substantial amount of base in the system that might have neutralized the acid production from the volcano's ashes. F i g u r e 5 - 1 3 . V a r i a b i l i t y i n T o t a l A l k a l i n i t y o f t h e P a m p a n g a r i v e r a n d i t s t r i b u t a r i e s f r o m D P W H d a t a ( a v e r a g e f o r t h e y e a r s 1 9 8 6 , 1 9 8 7 , 1 9 8 9 , 1 9 9 0 , 1 9 9 2 , 1 9 9 3 a n d 1 9 9 4 ) Minimum 400 7 10 11 16 17 18 19 28 31 32 33 37 39 43 44 45 48 52 57 headwaters stations mouth 89 F i g u r e 5 - 1 4 . V a r i a b i l i t y In T o t a l H a r d n e s s o f t h e P a m p a n g a r i v e r a n d i t s t r i b u t a r i e s f r o m D P W H d a t a ( a v e r a g e o f t h e y e a r s 1 9 8 6 , 1 9 8 7 , 1 9 8 9 , 1 9 9 0 , 1 9 9 1 , 1 9 9 2 , 1 9 9 3 , 1 9 9 4 ) 400 . f l 600 M i n i m u m M e a n M a x i m u m 7 10 11 16 17 18 19 28 31 32 33 37 39 43 44 45 48 52 57 headwaters stations mouth 5.3.3 Total Dissolved Solids and Chemical Oxygen Demand Figure 5-15 shows the variability of TDS, while Figure 5-16 presents the fluctuation of mean TDS concentration, along the Pampanga river and its tributaries. Comparison among mainstem stations revealed no significant differences (p<0.05) for the falling limb of the high flow period, but in the next two periods, significantly higher (p<0.05) values were registered by the four stations nearest the mouth of the river, and significantly lower values were registered by the four stations nearest the headwaters. This split in the middle during both the low flow and the beginning of the rainy season may be attributed to the contribution of very high TDS water from the lahar-covered areas. From the leaching studies conducted by Imai et al (1993) and the characterization of volcanic debris from Mt. Pinatubo by Bernard et al (1991), it was evident that lahar-covered areas contained a large amount of soluble salts. However, another possible reason that might have caused the high TDS values for the stations near the mouth of the river as compared to the more upstream stations, is that the lowermost stations are subjected to sea water (which contains higher amounts of TDS than fresh water) backflow during high tide. The combination of the effect of lahar and sea water intrusion is illustrated in the stations downstream of Station 42 (low flow graph of Figure 5-15). Generally, the TDS values for mainstem stations 90 t « s 8 8 8 8 8 ° CN {SI x- ^ 8 8 8 8 8 § ° CO CM CM r- ^ O O O O O O O o in o w o in co CM CM ^-10 O) c co Q. E CQ Q . 0) <*-O CO E Q CD 1- *-< u c >» CO >. k -> !5 CQ ' C CQ > IO T -£ 3 i i w TDS N_TD _TDS z ' < UJ 5 O • < o oo O •C _ i t EE g» f = o) co o 8 o in ^ 8 8 ° CM T -(iudd) SQi (ujdd) s a i <-a-o <-o—o 3 <n> T3 O u_ °? o o o o co m o o o o o o o co cn r-(uidd) s a i 91 increased from the end of the rainy season, through the dry season, and decreased in the beginning of the next rainy season. This presumably was due to the dilution effect of the discharge which is supported by the significantly (p<0.05) negative correlation between TDS and discharge. Comparison among tributary stations revealed significant differences (p<0.05) in TDS values during all three periods. The effect of discharge on the TDS concentration explained for mainstem stations, applies as well to TDS in almost all tributary stations, where the trend is of increasing TDS concentrations in the low flow period and decreasing again during the rainy season. There are however exceptions to the trend, among them are Station 4 which always had an extremely low value, and Stations 42 and 43 with extremely high values, in all periods. The forested catchment area and absence of major sources of TDS in the catchment, may explain the low values for Station 4. At Stations 42 and 43, TDS concentration decreases from its peak during the falling limb period and further decreases during the beginning of the rainy season. As these two stations have catchments affected by lahar, during the falling limb period, lahar deposits in Mount Pinatubo have been dislodged and materials contributing to the TDS are washed into the streams by rainwater, making the concentration of this material high. However, when the dry season sets in, rainwater is no longer there to wash away these materials and stream water will be supplied mainly by groundwater, thus the lower concentration during low flow. During the onset of the rainy season, there is a dilution effect and therefore the concentration goes even lower. When heavy rains and typhoons occur, some of the lahar would be loosened again, and as a result the TDS increases. When values from this study as presented in Figures 5-15 and 5-16, and compared with values obtained from DPWH (Figure 5-17), the observation that TDS values are greatly affected by lahar is further supported. A comparison of the TDS values in the present investigation with literature data are presented in Figure 5-18 which shows a slight trend of increasing TDS values < 3 2 co •o D_ Q E p CO CO •c CO "3 .Q - C CO T3 c CO > he CO CO c CO C L E CO 0_ CD o CO Q I-c .0. CO 5 LO CO (uidd) s a l a U 5 5 5 © • < < r > © <n> <a© <ao o <a> s o <-o-o o •0> 8 CD 1 1 ^ CM (uidd) s a i (uidd) s a i o - o <-a—© <-a—© <-o—© a a <-a—© CO 9 ( m d d ) s a i CM ( a i d d ) s a i ( L u d d ) s a i 93 Figure 5-18. Comparison of TDS in selected stations along the Pampanga river and its tributaries from four sources in four different periods 400 300 •=• 200 w Q t— 100 0 -I UPRP (1962-1973) O Maximum • Minimum H ! 1 1 1 1-• H 1 h * 6 H 1 1 1 1 h 400 i 300 1 E. 200 co Q H 100 0 Liongson (1976) < I - o * ODry • Wet — i • •-• u 1 1 1 h - — — \ —I 1 1 <r 1 1 1 1 H 400 300 — 200 co Q 100 0 DPWH (1986-1992) i 1 1 -+- H 1-1 1 0 § 1 J 1_J ODry • Wet -t h -\ 1 1 h 400 300 •=• 200 co a H 100 This Study (1993-1994) O Falling Limb • Dry Season A Rising Limb ° ' S 1 8 L l S e 2 S 8 6 1 1 1 1 1 1 1 1 1 1 1 1 1 8 10 11 17 18 19 21 27 28 33 37 39 44 4 6 7 Headwater Stations Mouth 94 since 1962. Although a statistical comparison cannot be made due to limitations of the published data, increased load of TDS in the Pampanga river system over time is indicated. Figure 5-19 demonstrates the variability of COD concentrations, and Figure 5-20 presents the fluctuations in mean COD concentrations along the Pampanga river, in the three periods. For the mainstem stations, the four stations nearest to the mouth registered significantly (p<0.05) higher COD concentrations in both the dry season and the beginning of the rainy season. Although this may be related to the decreased water volume during the low flow period which concentrated the dissolved substances in water, and to the increase in oxygen-demanding substances as a result of the flushing effect of rainfall during the onset of the rainy season, the presence of chlorides as indicated by the high TDS content, may have interfered with the COD tests. This may occur when the dichromate reagent is consumed during the oxidation of chloride to chlorine (APHA, 1985). The significant (p<0.05) positive correlation between TDS and COD strengthens this possibility. The fluctuations in mean COD concentrations along the Pampanga river are similar in all three periods. The high mean COD concentration during the rising limb period indicates the increased input of organic substances that can consume oxygen, as a result of being washed in by rainfall. The exception to this trend is observed for the segment of the river between Stations 8 and 11. The decrease in COD concentration in the rising limb period between the stations, may be attributed to the release of water from the dam at Station 8 during the start of the rainy season, the volume of which diluted the oxygen-demanding substances. There also appears to be a gradual increase in mean COD concentration in the segment of the Pampanga river from Station 10 to Station 40. Since this increase occurs during all three periods, and at stations upstream of any salt wedge and chloride effects from sea water, an increase in pollutant load to the river is indicated. 9F 8 8 ° CD O c o '-3 2 5 E o u (0 >> _ V) Q t_ o a? o 5 . E to to E '= 1? CO o. > £ 3 D) m co O O O O, O I £=2 3 5 5 5 O • < "5 TJ O •e _ CD 2~ « l u: ? ^ = O) co 8 8 8 8 8 ° N W ^ t -(i/Bui) aoo 8 8 8 (I/BUI) aoo 8 8 8 8 8 ° C N C M T - T -( I /BUJ) aoo 96 In terms of the tributary stations, significant (p<0.05) differences were observed among the stations in all three periods. When the stations were arranged according to COD values, it was observed that several stations have once again shown consistency in their relative position in the distribution of COD concentrations in all the periods. At the lower end of the distribution are Stations 4, 7, and 10, which are headwater stations, with catchment areas predominantly consisting of woodland and grassland land-uses. At the upper end of the distribution are Stations 13, 14, 42, and 43. These stations are those situated in the city of Cabanatuan with catchment areas consisting of mixed agricultural and settlement land-uses, while the two latter stations are in the lahar-affected areas. Following the stream water classification used by Dojlido and Best (1992), the COD values registered by the Pampanga river system fall between Class I (< 40 mg/1) and Class II (< 60 mg/1), suggesting clean waters for the river system. However, streams affected by lahar, with observed COD values exceeding 100 mg/1, may be considered as very polluted waters based on COD concentration. A note of caution must be used however in the interpretation of the data, since the chloride contributed by the volcanic fallout, which may have consumed some of the dichromate in the COD test, may have resulted in the higher COD values of streams affected by lahar. 5.3.4 Nutrients (Nitrate-N and Ortho-phosphate) and the risk of eutrophication Nitrate-nitrogen Figure 5-21 illustrates the variability of N 0 3 - N for all the stations, while Figure 5-22 shows the fluctuation in mean N O 3 - N concentration along the Pampanga river, in all three periods. For mainstem stations, a significant (p<0.05) difference was only observed in the low flow period, where Station 18 registered a significantly higher concentration. This station is downstream of the 9* (l/Biu) N-3»BJJ!U (l/Bu|) N-3JBJHU (l/Biu) N-aiBJl!" 98 highly-populated area comprising Cabanatuan City and the suburbs of Sta. Rosa and San Leonardo. Sewage treatment plants are non-existent in these settlements, thus, surface runoff from the public markets, slaughterhouses and to a less extent, from the residences, enters the Pampanga river or the tributary streams. These settlements might have contributed the high nitrogen input to the water, resulting in a higher N O 3 -N concentration in Station 18 as compared to other stations. This high concentration of N O 3 -N was diluted further downstream of this station. Although significant (p<0.05) differences were observed among N O 3 -N levels for tributary stations in all three periods, when all the stations were arranged according N 0 3 - N concentrations, no station was consistent in its position in the distribution. However, the common geographical distribution of the stations exhibiting significantly higher N O 3 -N concentrations in the different periods would explain the differences. For example, at the end of the rainy season, the two stations with significantly higher nitrate concentrations were stations 30 and 36, both in the western part of the basin and both having catchments dominated by agricultural land-use. In the low flow period, Stations 33 and 37, along the Talavera river, as well as Stations 13, 17, 19, 45, and 46, along the eastern part of the basin registered significantly higher (p<0.05) N O 3 -N values. At the beginning of the rainy season, Stations 7, 21, 27, 45 and 48, all in the eastern portion of the basin were those with significantly higher N O 3 -N values. This geographical relationship is important, especially since the precipitation pattern in each station is highly influenced by its geographical location. The eastern portion of the basin usually lags behind for a few weeks due to the effect of the Sierra Madre mountain ranges. Streams here still have good flow while streams in the rest of the basin are starting to dry up. Thus, the agricultural cropping pattern in these areas lags somewhat and this lag might have caused the difference in the effects of various land-uses on the concentration of N 0 3 - N in streams. 99 A limited comparison of the present N C V N values to historic data can be carried out with fragmentary data: Bautista (1964) gave values of < 0.01 mg/1 N 0 3 - N for five sampling times in 1964 for Station 57 of the Pampanga river. The same station presently has a high of 2.21 mg/1 of NO3 -N. Furthermore, the seven stations (4,7,8,11,21,28,33) included in the study of Liongson (1976) on the Upper Pampanga River Project which consistently registered values of < 0.05 mg/1 in the dry season of 1976, now register 0.9, 2.4, 1.4, 2.8, 1.6, 3.0, and 2.6 mg/1 N O 3 -N, respectively. Although a statistical analysis cannot be made on the above-mentioned data, the comparison reveals that N 0 3 - N in several reaches of the river has increased since 1964, indicating the possibility of recent pollution in the system. Ortho-phosphate Figure 5-23 illustrates the variability of orthophosphate for the Pampanga river and its tributaries, while Figure 5-24 presents the fluctuations in mean ortho-phosphate concentration along the Pampanga river, for the three periods. For the mainstem stations, significant differences (p<0.05) were revealed during the low flow period. The four stations nearest to the mouth registered significantly higher phosphate values than the four nearest the headwaters. The dividing line between these two groups of stations is the tributary Rio Grande de Pampanga, just downstream of Station 43, which contributes the lahar-carrying water that is very high in phosphates. The influence of lahar in increasing the phosphate levels in water may be explained when the P content of 6.67 parts per thousand (ppT) to 7.56 ppT in the lahar from Mt. Pinatubo (Bernard, 1991) is compared to the O.OlppT to 0.06 ppT in the agricultural soils in the area (De Datta, 1988). The high P concentration therefore may pose a risk for stream eutrophication. In terms of the tributary stations, significant differences (P<0.05) were observed in all three periods, when the stations were arranged according to ortho-phosphate concentration, it was 101 observed that some stations were consistently in the same positions in the distribution, in all three periods. At the low end of the range are Stations 4, 7, and 10, all headwater or near the headwater stations, with predominantly woodland and grassland catchments. At the opposite end of the range are Stations 13, 42, 43, 46, and 48. The first of these stations is in Cabanatuan City and the last two are in the fast-growing town settlement of San Miguel. These stations have predominantly agricultural catchments with sizable settlement portions. Stations 42 and 43 are stations carrying the phosphate-rich lahar. The risk of eutrophication in the Pampanga river system It was assumed that the nutrients taken up and used by algae reflect the relative composition of the elements in their cellular material, resulting in the mass ratio of the elements 106C:16N:1P, or the nutrient concentration ratio of 7.2N:1P, as the widely cited standard reference values for assessing the limiting nutrient in waterbodies (Ryding and Rast, 1989). The present investigation measured the N O 3 -N and ortho-phosphate concentrations (in units of mg/1) in the Pampanga river system, thus, the latter reference value was used in the following discussion. Figure 5-25 indicates that in general, the potentially limiting nutrient for eutrophication in the mainstem is, P for stations upstream of Station 28, and N for those stations downstream of the same station. The effect of Mt. Pinatubo through the phosphorus-rich lahar which enters the mainstem on Station 44, is the reason for the low ratio in stations near the mouth of the river. Although Station 28 is not affected by lahar, it still registered a low N:P ratio, suggesting that a major source of P may exist in the catchment of this station. For the tributaries, N:P ratios as presented in Figure 5-26 would indicate that land-uses in the different catchments may be contributing different ratios of nitrogen and phosphorus to the streams. 102 Figure 5-25. N:P ratio of mainstem stations in three different flow periods 10 •2 6 B a. z 4 2 0 i LU , rt • Falling Limb • Low Flow • Rising Limb 8 11 16 18 28 44 53 56 57 headwater stations mouth Figure 5-26. N:P ratio of tributary streams in three different flow periods 20 • Falling Limb • Low Flow • Rising Limb i i hi It •J, .uL:uk. L • iiL.m.r i . r r l . r f l l ,r . , H . 7 10 13 14 17 21 27 30 32 36 37 39 43 45 46 48 49 50 51 52 54 headwater stations mouth In terms of temporal changes in the limiting nutrient, the results in the present study was in contrast to results of Liongson (1976) who concluded that nitrate, rather than phosphate was the more limiting nutrient in the river system. Since the present study proves that phosphorus was the more limiting nutrient in stations not affected by the phosphorus-rich lahar, the present study clearly shows that there might be an increase in the nitrogen inputs in the basin, and therefore, a potential nitrogen contamination problem in many of the streams. 103 Aside from N and P concentrations, physical factors are also important in influencing eutrophication in rivers. Among the factors discussed by Bowles (1980), the velocity of the river, and the influence of light, must be considered in explaining the risk of eutrophication in the Pampanga river system. During the dry season, the velocities of the streams are low, with some tributaries becoming totally dry at times; the water is clear and light can penetrate the waters. This may explain the observations that streams during the dry season have highly visible algal blooms, indicating that the risk of eutrophication was higher during the low flow period than in the high flow periods. Furthermore, during the high flow periods, even when N 0 3 - N is high, the lack of light due to the turbidity of waters in the river system (owing to the erosion in the basin), may limit algal growth. 5.4 The water quality of the Pampanga River System in perspective From the data presented, it is evident that there is considerable variation in water quality in the Pampanga river and tributaries, in both the spatial and temporal dimensions. In terms of the spatial differences, there are clear indications that stations with relatively high proportion of a certain land-use classification in their watershed seem to exhibit similar water quality conditions. The relationship of land-use and water quality has been mentioned as a possible explanation for much of this spatial variation. This relationship therefore is very important and warrants further analysis, thus, it is quantified and explained in the next chapter. Evidence is revealed that the eruption of Mt. Pinatubo had a strong effect on water quality, especially on streams that run along lahar-covered areas. Since the eruption influenced almost all water quality parameters, it has to be considered in the discussion of land-use and water quality in the next chapter. 104 In the short-term temporal dimension, it was shown that seasonal variation of water quality parameters does exist. This variation is traceable largely to the rainfall pattern or to the resulting discharge fluctuations, and the sporadic eruption of Mt. Pinatubo. In terms of pollution, although the values registered by the stations in the study were most often within the acceptable values for Class C waters, there are indications that pollution loads to the Pampanga river system have increased over time. In order to put the values in the study in perspective, they were compared with those of two water systems that are believed to be polluted. Table 6-2 shows this comparison. Laguna lake and the rivers in the island of Cebu have been considered to be polluted and this may be justified because their DO levels sometimes get lower than the allowable value. This does not hold true for the river system studied, as its DO level has generally been above the DO value of 5 mg/1, which is the lower limit considered healthy for fish. However, the values for COD, N 0 3 - N , and Ortho-P0 4 are higher than those of polluted rivers. It is clear therefore that some selective water contamination problem exists in the basin. To be able to ascertain the causes of such pollution, a study on the relationship of water quality and point and non-point sources of pollution was carried out. This is the theme of the following chapter. Table 5-1. Comparison of water quality parameters from study results with two polluted river systems in the Philippines* (All values in mg/1 except pH which are in pH units) Parameter Pampanga Pampanga Laguna Laguna lake Cebu mainstem tributaries lake' tributaries2 rivers3 pH 6.18-8.26 (6.69) 6.02-8.98 (6.84) 7.10-8.70 7.30-8.00 7.20-8.10 TDS 58-441 (132) 31-940 (162) 154-497 150-180 DO 4.5-7.9 (6.3) 5.4-7.3 (6.4) 6.1-12.0 1.10-7.30 0.51-7.46 COD 0-333 (35) 0-1650 (37) 11-21.4 5.28-12.54 N 0 3 - N 0.00-3.20 (0.71) 0-5.0 (0.68) 0.04-0.20 Ortho-P0 4 0.01-8.00 (0.27) 0.01-4.58 (0.29) 0.10-0.87 0-0.03 *Values in parenthesis are averages 1 Barril (1990) 2 Laguna Lake Development Authority (1995) 3 University of San Carlos (1995) rt>5 Chapter 6. LAND -USE AND W A T E R Q U A L I T Y INTERACTIONS Historically, pollution abatement in the region has been directed to controlling point sources. However, the lack of data and an understanding of the influence of non-point sources on river quality has been a limiting factor in enforcing regulations of point sources. The case of the Central Fermentation Industries Corporation (CFIC) and the Far East Alcohol Company (FEACO), two alcohol distilleries close to Station 57 illustrates this link between point sources and non-point sources. A memorandum to the Director of the E M B by the RTD in August 1990 (DENR, 1990) addresses the complaints of fishermen against the point sources (CFIC and FEACO). In the memo, the complaints include fish kills in fishponds, low productivity of prawn ponds, and a reduction of rice yields along the Pampanga river, ever since the two fermentation plants started operation. However, the same memo stressed the difficulty of ascertaining the contribution of the two plants to the alleged problems, as non-point sources (NPS) upstream may also influence the water quality of the river. The NPS enumerated included runoff from agricultural, built-up, and denuded forest areas. Although the complaints were lodged very regularly, and the plants were closed three times since 1990, the management is always able to reopen the plants (Manila Bulletin, 1994). The complaints again resurfaced in 1994, and in an open letter to a columnist (Tempo, 1994) regarding the same pollution allegations, the new RTD emphasized the same NPS upstream, which up to that time was not yet studied, as potential sources adversely affecting water quality. It seemed therefore that the plants were allowed to continue their operation. However, in February of 1994, a senator (who is from the allegedly affected area) urged the DENR secretary to have the plants closed (Standard, 1994) and in June 1994, the plants were closed by the military, with the help of local officials (Malaya, 1994, Philippine Daily Inquirer, 1994, Manila Bulletin, 1994). 106 The management of the companies claimed that the DENR was being used by the local officials for election purposes (Malaya, 1994), as local election were due in May of that year. Although the plants were closed at that time, the real problem (the lack of data to support claims on either side) has not been resolved. In the basin, the effect of non-point sources on the quality of the streams is still unknown. This chapter therefore, which analyzes the interaction between non-point sources and water quality in the Pampanga river, is a contribution to improve the understanding of the problem. The dramatic land-use changes in the Pampanga River Basin were clearly illustrated in Chapter 3, and the water quality conditions were illustrated in Chapter 5. This chapter analyzes the interactions between land-use and water quality in the basin, drawing upon the empirical relationships between land-use as an index of non-point sources of pollution, and water quality in the basin during the period of the study. The relationships established here will set the stage for predicting results from alternate scenarios, a topic discussed in later chapters. From the water quality parameters discussed in the preceding chapter, five were selected (based on the suggested relationships with landmse presented in the preceding chapter) to illustrate land-use impact on water resources. They include pH, TDS, nitrate-N, ortho-phosphate, and COD. 6.1 Cumulative contributing areas and buffer regions The statistical analysis of mainstem stations used the concept of cumulative contributing areas. Since the catchment area that is upstream of a water quality station is also a contributor to the water quality of the downstream station and not only the adjacent land-use, the idea of using cumulative contributing areas was found useful. The cumulative area for a given station is the addition of all areas upstream. 107 To improve the sensitivity of the investigation, a buffer analysis was also undertaken to show the effect of land-use on water quality. To carry out this analysis, the digitized streams were divided into minor and major streams. Two groups of streams, the first group containing both minor and major streams (referred to as all streams ), and the second group containing only the major streams (referred to as major streams) were buffered by three distances (1000 m, 500 m, and 250 m), resulting in six buffer combinations. These six buffer areas and the total catchment area, are hereafter referred to as area classifications. Appendix Table 6-la presents the cumulative contributing areas for the stations used in the study. 6.2 Land-use and Water quality interactions: Land-use cover as index of non-point source of pollution (NPS) This section discusses the relationships between the different land-uses as an index of NPS and water quality parameters. The proportions (%) of each land-use discussed, are in terms of their decimal equivalents; a value of 0.50 means that the proportion of that land-use is 50% of the area classification being considered. Trend lines that are used to illustrate the degree of relationship may be linear or quadratic, but the line with the relatively higher R 2 is presented in the figure. 6.2.1 Relationship between rice field and water quality The proportion of rice field in the catchment area of tributary stations was only significantly correlated (p<0.05) to pH and nitrate-N, among the five water quality parameters. Although these relationships were found to occur in all area classifications, these were limited to the rising limb of the high flow period. The average R 2 between rice field and pH, with respect to the area classifications ranged from 0.49 to 0.57. Figure 6-1 reveals the negative relationship 108 between % rice field and pH, as the trend line indicates. In the mainstems stations, Figure 6-2 shows that pH remained relatively stable from headwater to mouth of the river even when % rice field increased, indicating the minor influence of rice field to pH in streams. Figure 6-1. Relationship between % ricefield and pH of tributary streams during the Falling Limb of the High Flow Period in the Total Catchment Area 1.20 1.00 2 0.80 « I 0.60 SS 0.40 0.20 0.00 • • • _ • • y = 0.5731 x2 - 9.5155x + 39.832 • " R2 = 0.49 • • • — ; ; 1 i 1 1 A t 7 7.2 7.4 7.6 7.8 8 8.2 8.4 p H The relationship of the proportion of rice field in catchment area and nitrate-N concentration in tributary streams is represented in Figure 6-3. The relationship is negative as the trend line indicates, giving significant (p<0.05) correlation R 2 ranging from 0.46 to 0.64 with respect to the area classifications. Figure 6-4 illustrates the changes in nitrate-N concentration along the Pampanga river. The general trend was that the nitrate-N concentration of the river decreased toward the mouth as proportion of rice field increased. The assumption that rice fields are the main sources of nitrate-N which eventually would have reached the streams therefore cannot be supported by the data. Rather, the rice fields became sinks for nitrate-N, thus 109 Figure 6-2. Changes in pH of the Pampanga River during the Rising Limb of the High Flow Period relative to the cumulative % rice fie Id in the Total Catchment Area 0.00 4- t ^ J 8 11 headwater ^ M -16 18 28 44 m a i n s t e m s t a t i o n s 53 56 57 mouth 6.5 the negative correlation. Consideration should be given to the fact that during the early part of the rising limb, the rice fields are still collecting water from rainfall for rice planting, thereby catching most of the nitrate-N that might come from runoff. The lack of significant correlation during the low flow and the falling limb of the high flow further supports this explanation, since runoff and the nitrate-N from it are absent in these periods. Another reason that might explain the negative correlation between rice fields and nitrate-nitrogen during the rising limb is the fact that nitrate forms under oxidizing conditions, and therefore it would be expected to be higher in water immediately after the dry season, especially from rice fields. In the case of settlements, nitrates would tend to be more uniform throughout the year, thus the lack of correlation in all the periods. When one considers the fact that the major conversion of rice fields is to settlements, the case that a decrease in rice fields would bring about increases in settlements will ultimately translate to increased nitrate-N in stream waters. 110 Figure 6-3. Relationship between % ricefield and nitrate -N concentration of tributary streams during the Rising Limb of the High Flow Period 1.00 0.80 1 0.60 B OI tj * 0.40 0.20 0.00 * • * y = 1.2647x2-2.118x + 1.1232 • • # = 0.43 • • • • v -1 i ; — • • • 1 •„ , t • • • 0.1 0.2 0.3 0.4 0.5 0.6 0.7 ppm nitrate-N 0.8 0.9 Figure 6-4. Changes in nitrate-N concentration of the Pampanga River during the Rising Limb of the High Flow Period relative to cumulative % ricefield in the Total Catchment Area 8 11 headwaters mainstem stations 6.2.2. Relationship between settlements and water quality It is only with stream ortho-phosphate concentration that the proportion of settlement gave significant (p<0.05) correlation to any water quality parameter. The result that these positive Ill correlations were only limited to the 500 m buffer zone on major streams points to the fact that settlements within 500 meters from the streams are major contributors of ortho-phosphates. Farther than 500 m from the streams, settlements may produce large quantities of phosphate, but it might be intercepted before reaching the stream. The characteristic of the phosphates to adsorb to soil particles supports this observation. The fact that the relationship was evident in all three seasons ( R2 values of 0.58 for the falling limb, 0.61 for low flow, and 0.51 for the rising limb), further supports the observation. The changes in ortho-phosphate concentration in the mainstem, following the trend for settlements as illustrated in Figure 6-5, supports the argument that settlements are major contributors of ortho-phosphates. 6.2.3 Relationship between woodland and water quality The proportion of woodland in the catchment area showed a significant (p<0.05) correlation with pH and nitrate-N concentration of tributary streams. The relationships were found only during the rising limb of the high flow period, although they occurred in all area classifications (total catchment area and all buffer zones). The R2 values for different area classifications ranged between 0.49 to 0:61 with the larger areas giving higher values. Figure 6-6 illustrates the case with pH. The trend line indicates the existence of a weak positive relationship between pH and woodlands, while the changes in pH relative to woodlands, as illustrated in Figure 6-7, supports the argument that woodland has only a minor influence on pH. 112 Figure 6-5. Changes in ortho-phosphate concentration of the Pampanga River during the Rising Limb of the High Flow Period relative to the cumulative % settlement in the 500 m buffer zone along major streams headwater mainstem stations Figure 6-6. Relationship between % woodland and pH of tributary streams during the Rising Limb of the High Flow Period in the Total Catchment Area 0.70 •, 0.60 A A y = 1.0956x-7.2392 A 0.50 R2 = 0.3578 A •a c cs 0.40 A I 0.30 • A A A 0.20 A ,. A 0.10 • A A 0.00 A I A—I A 1 —I A - — l A A I 1 6.6 6.65 6.7 6.75 6.8 6.85 6.9 6.95 7 113 Figure 6-7. Changes in pH of the Pampanga River during the Rising Limb of the High Flow Period relative to cumulative % woodland in the Total Catchment Area 0.50 0.40 + 1 0.30 + * 0.20 0.10 0.00 4 i % w oodland — A — mean-pH headwater 6.9 6.8 - 6.7 - 6.6 6.5 mainstem stations The very high R2 values for woodlands and nitrate-N in all area classifications, ranging from 0.67 to 0.89, as illustrated in Figure 6-8, indicate that the woodlands are major sources of nitrogen. It is surmised that the predominance of Leucaena (a fast-growing nitrogen fixing tree) in the reforestation projects, may have been a major contributor of nitrogen. Since some of these woodlands double as pasture lands, nitrogen from animal wastes might play a part in explaining this major influence of woodland on nitrate-N of streams. Changes in nitrate-N concentrations of the Pampanga river (illustrated in Figure 6-9) further point to this explanation. The fact that this relationship occurred only during the rising limb of the high flow period indicates that the nitrogen, which might have been trapped in the land during the low flow was washed to the streams when the rains arrived. 114 6.2.4 Relationship between grassland and water quality The proportion of grassland in the catchment area is significantly (p<0.05) correlated to pH and nitrate-N concentration of the streams. Although the relationships were weak, as illustrated in Figures 6-10 to 6-13, the fact that correlation occurred only during the rising limb of the high flow period and were limited to the 500 meter buffer along major streams suggests that the activities in this land-use, such as pasture and vegetable production, release nitrogen which is washed into the stream during the rainy season. However, these same activities may also take up nitrogen through animal feeding and crop harvesting. Thus, the relationship with grasslands was not as strong as that found with woodlands, where it would take years before any harvesting could be performed. Figure 6-8. Relationship between % woodland and nitrate-N concentration of tributary streams during the Rising Limb of the High Flow Period in the Total Catchment Area 0.8 | 0.6 § * 0.4 0.2 0.00 y=0.8956x+0.1876 R2 = 0.802 • A 0.10 0.20 0.30 0.40 ppm nitrate-N 0.50 0.60 0.70 115 Figure 6-9. Changes in nitrate-N of Pampanga River during the Rising Limb of the High Flow Period relative to the cumulative % woodland in the Total Catchment Area I % w oodland -mean no3 + 0.5 % + 0.4 £ + 0.3 | a. 8 11 headwater 56 57 mouth mainstem stations Figure 6-10. Relationship between % grassland and pH of tributary streams during the Rising Limb of the High Flow Period in the 500 m buffer along major streams y = 2.7047x2 - 36.029x +120 R2 = 0.3301 6.6 i T ' * ~ r * - -6.65 6.7 Hk-6.75 6.8 pH r4 * A , 6.85 6.9 6.95 116 Figure 6-11. Changes in pH of the Pampanga River during the Rising Limb of the High Flow Period relative to cumulative % grassland in the 500 m buffer zone along major streams 0.40 0.30 •o e « V, 0.20 + 0.10 + o.oo A % grassland —•—mean-pH 8 11 headwater 16 18 28 44 mainstem stations 53 56 57 mouth 7 6.9 6.8 6.7 • 6.6 -- 6.5 Figure 6-12. The weak relationship between the proportion of grassland area in the 500 m buffer zone along major streams and nitrate-N concentration of tributary streams during the Rising Limb of the High Flow Period 0.5 ppm nitrate-N 0.7 0.8 0.9 117 Figure 6-13. Changes in nitrate-N concentration in the Pampanga River relative to the cumulative % grassland during the Rising Limb of High Flow Period in the 500 m buffer zone along major streams 0.50 0.40 1 0.30 (A in S oi 0.20 ss 0.10 0.00 8 11 headwater l % grassland -mean no3 0.80 + 0.60 0.40 £ E a. a. 0.20 0.00 mainstem stations 6.2.5 Relationship between wetlands and water quality Although wetland areas can improve water quality, no such relationships resulted from the study. This may be attributed to the very small area classified as wetland, only 1.2 % of the total basin area, which is further distributed almost evenly in all of the catchments. 6.2.6 Relationship between lahar-covered areas and water quality The influence of lahar-covered areas on ortho-phosphate is illustrated in Figure 6-14. It can be observed that the concentration of ortho-phosphate abruptly increased after the tributary (Station 43) contribution of lahar-rich water. The concentration then decreases slightly as the water is diluted further downstream. This trend was the same in all flow periods and area classifications. 118 Figure 6-14. Changes in ortho-phosphate concentration of the Pampanga River relative to cumulative % lahar-covered areas during the Falling limb of High Flow Period in the 500 m buffer zone along major streams Lahar covered areas registered significant (p<0.05) correlation with TDS and COD concentrations of tributary streams, during all the three flow periods and in all area classifications. Average R 2 values for TDS ranges from 0.96 for falling limb, 0.86 for low flow, and 0.95 for rising limb, while values for COD are 0.98 for falling, 0.79 for low flow and 0.88 for rising limb. The very high correlation between TDS and COD within the lahar-covered areas may be attributed to the fact that lahar contains solids that are dissolved by water. This is supported by the very high levels of chlorides in lahar, as cited in the preceding chapter. These solids which are both measured in terms of TDS and COD is the reason for these two parameters being very highly correlated to each other (R2 = 0.92 for falling limb, R 2 = 0.91 for low flow, and R 2 = 0.72 for rising limb). Figures 6-15 and 6-16 show a clear trend, where TDS and COD concentrations abruptly increase downstream of the main contributor of lahar, the tributary stations 43, and then follow the decrease in the proportion of lahar-covered area toward the mouth of the river. The higher correlation during the high flow periods and the lower correlation during the low flow period 119 are the result of rainwater being present during high flows and absent during low flows. This water dissolves the solids in lahar and brings about the elevated levels of TDS and COD in stream waters. This fluctuation in rainfall has an effect on the variations in the correlation that result from the different area classifications. Figure 6-15. Changes in TDS concentration of the Pampanga River relative to cumulative % lahar-covered area during the Falling Limb of the High Flow Period in the 500 m buffer along major streams 0.06 y 0.05 •-0.04 o 0.03 -ra it 0.02 -0.01 --0.00 -imam % lahar —A—mean tds 8 11 headwater -+- •+-16 18 28 44 mainstem stations 53 56 120 115 110 105 - 100 - 95 90 co Q H E a. a. 57 mouth Figure 6-16. Changes in COD concentration of the Pampanga River relative to cumulative % lahar-covered areas during the Falling Limb of High Flow Period in the 500 m buffer zone along major streams 120 6.3 Land-use Activities and Water quality interactions: The case of animal farms Although several point sources of pollution exist in the basin, the major ones are animal farm enterprises. Determining the effect of these point sources, however, needs an above-and-below approach, but since there were thousands of farms, it was impossible to investigate the individual contributions of each. Therefore, in this section, the analysis and discussion involved the cumulative effect of these farms in each catchment. The barangay centroid of population was used as the geographical location of data on animal farms. Addresses pf the farms were traced to the barangay, the largest scale possible for assigning their location. The centroid of the barangay was determined on the 1:50,000 map and all information relating to the barangay was related to this centroid. Animal enterprises in the basin can be divided into commercial and backyard production, the study focused on the commercial farms. The lack of spatially referenced information is the reason for not including the backyard production in the basin at this point in the study. Most of the census data on backyard animal production are based on provincial averages, a scale that is not consistent with the scale of the present study. The differentiation between a backyard and a commercial enterprise was based solely on the classification used by the Bureau of Agricultural Statistics, which furnished the data. A l l discussions involving animal production that follow, therefore, just relate to the commercial enterprise. To simplify the analysis and discussion, the different species of animals were grouped together as follows; ruminant animals were subdivided into the large ruminants (cattle and buffalo) and the small ruminants (sheep and goats), while the monogastric species were subdivided into hogs and poultry (ducks, layers, broilers). 121 6.3.1 The effect of animal farms on water quality Effect on pH During the falling limb of the high flow period, among the animal population densities, it was only the hog population density that gave a statistically significant (p< 0.05) correlation with the pH of the streams. Furthermore, all of these significant correlation occurred in the 250 and 500 metre buffer zone of all streams and major streams suggesting that the hog farms near the streams have more influence on the variation in water pH than those in areas far from the water bodies. This is not surprising since most of the big hog farms are near the major streams, as illustrated in Figure 6-17. The correlation between number of hogs and pH may be attributed to the higher pH of swine waste (values presented in the succeeding section on animal waste management), than the water in which the waste is discharged into. Furthermore, during the falling limb of the high flow period, animals are larger as they are ready to be marketed. Since the animals are usually marketed after this peak season (Christmas holidays), during the low flow period, the hogs may not be there or are very small animals such that their effect on water quality will be less. A further explanation may be that during the low flow, there is no rainfall to wash the manure into the water. Effect on TDS and COD A weak but significant (p< 0.05) correlation was observed between animal density and TDS and COD for ducks. A logical explanation for this observation is that ducks are usually the only animal species considered in the study which stays a considerable amount of time on the water. This long contact time and the very possible constant agitation of the water might have resulted in the very high concentrations of COD and TDS. 121 123 Effect on Nitrate-N During the falling limb of the high flow period, the hog population density was the only one among other groups of animals which was significantly (p < 0.05) correlated with nitrate-N concentration of stream water. During the low flow period, the population densities of poultry species were the ones with significant (p <0.05) correlation to the nitrate-N concentration. However, during the rising limb of the high flow period, population densities of the ruminant species were the ones significantly (p <0.05) correlated with the water quality parameter. The explanation for the effect of hog population density on nitrate-N is similar to the effect of this poultry species on nitrate-N. During the low flow period, the densities of layers and broilers seem to be significantly (p <0.05) correlated with nitrate-N. As can be observed in Figure 6-18, these poultry species are not necessarily located near major streams, their effect on nitrate-N during low flow is therefore surprising. The only logical explanation is the fact that the majority of these poultry farms dispose of their dressing refuses/wastes, including carcasses of dead poultry, to the streams, as was personally observed in many cases. This might have resulted in a high nitrate-N in these streams. The fact that the significant correlation occur only in 500 and 1000 meter buffers on streams strengthen this argument, for it might not be very efficient to dispose of the wastes when the stream is some distance from the production enterprise. The same correlation was not observed during the rising limb since production of poultry usually declines during the rainy season. In terms of the ruminant species, their population densities had significant correlation (p < 0.05) only during the rising limb of the high flow since during this time, rainfall is present to wash away the wastes that might have accumulated on the pasture areas near the streams. Figure 6-19 and Figure 6-20 show the distribution of ruminant animals. 124 Figure 6-18. Distribution of commercial poultry farms in the Pampanga River Basin N u m b e r - o f B i r d s < 1 0 , 0 0 0 1 0 , 0 0 0 - 5 0 , 0 0 0 > 5 0 , 0 0 0 B a s i n B o u n d a r y P o m p o n g o R i ^ e r a n d T r i b u t a r i e s 3 0 K m N Figure 6-19. Distribution of commercial large ruminant farms in the Pampanga River Basin N u m b e r of A n i m a l s < 2 0 2 0 - 7 5 7 6 - 1 5 0 > 1 5 0 B o s I n B o u n d a r y P a m p a n g a R l u e r a n d T r i b u t a r i e s 3 0 K m Number oT Animals < 20 Bas in Boundary Pnmnnnnn Rluar and T r i b u t a r i e s 127 Effect on ortho-phosphate The absence of any significant (p < 0.05) correlation of ortho-phosphate concentration on streams indicates that the variations in ortho-phosphate concentration are largely the influence of the presence of lahar and settlements. The high ortho-phosphate concentration in the basin might be so high that additional impacts by animals cannot be observed. Furthermore, phosphates tend to adsorb to the soil and are not as mobile as nitrates (Manahan, 1990). 6.3.2 The animal unit equivalent (AUE) and water quality It is difficult to determine the simultaneous effect of all the animal species on water quality without a common unit of comparison. The A U E index was employed as the single unit of comparison, and with its use, the animal populations can be added together into a single number, based on the nutrient contribution of each species (Loehr, 1984). The conversion factors used for the A U E are presented in Table 6-1. The resulting A U E in the study was only correlated significantly (p<0.05) to nitrate-N, among the water quality parameters. These significant correlation occurred only during the rising limb of the high flow period and only in the 500 and 250 meter buffer zone along major streams. The relationship is illustrated in Figure 6-21. In all area classifications, the species highly correlated (p < 0.05) with the total A U E were always the hogs, the large ruminants and the layers. It is not surprising then that these three groups of animals were also the ones concluded to have influence on nitrate-N concentration of stream waters. 128 Table 6-1. Animal Unit Equivalents (AUE) used in the study* Anirnal Species buffalo cattle sheep and goat hog ducks and laying hens broilers Number of animals equivalent to one A U E i 2 4 15 125 1000 •Source: Loehr (1984) Figure 6-21. Relationship between AUE density and nitrate-N concentration of tributary streams during the Rising Limb of the High Flow Periodin the 500 m buffer zone along major streams 50 j 40 E & 30 -in w V Q . 20 Ill 3 < 10 0 • y =47.497x-9.7185 R2 = 0.5062 — i — A A —Air 0.1 0.2 0.3 0.4 0.5 ppm nitrate-N 0.6 0.7 0.8 0.9 tr in & LU < Figure 6-22. Changes in nitrate-N concentration of the Pampanga River during the Rising Limb of the High Flow Period relative to the cumulative AUE density in the 500 m buffer zone along major streams 14 12 E 1 0 8 aue/sqkm mean no3 8 11 headwater 28 44 mainstem stations 56 57 mouth 0.80 0.60 z • w 0.40 £ c E a. 0.20 a 0.00 129 6.3.3 Waste management in hog farms To understand the interactions between animal farms and water quality, waste management practices of the farms should be examined. This discussion is focused on hog farms since it is the only animal enterprise with waste management records available. The pollution of streams by the farms may be the direct result of inadequate storage or handling of manure. However, records at the DENR reveal that complaints about water pollution from animal farms were related to odour problems and fly infestations in communities close to animal farms. Since it was difficult to lodge a complaint on just the odour alone, the water, the fishes and the farm yields were added grievances. Although the evidence for livestock manure and wastes being the cause of poor water quality in the basin is perceived to be circumstantial, caution is used in reporting the incident statistics in this chapter derived from the reports obtained from the DENR, since the recording of pollution incidents does not necessarily reflect the true level of farm pollution. The records on waste treatment facilities that were studied showed that very few farms have satisfactory treatment procedures based on efficiency of waste treatment, while a considerable proportion of farms do not even use their waste treatment facilities. This suggests that the real level of pollution from farms may be greater than incident numbers indicate. Reported incidents are, however, important indicators of pollution problems and may be regarded as a reasonable guide to the causes of serious pollution incidents and the measures needed to prevent them. Although the most effective means of reducing point-source pollution from hog farms is to upgrade the waste storage facilities and reduce waste volumes, the following history, and wastewater characterization, indicate that animal waste management in the region will be a growing concern. 130 Historical examination of waste management of hog farms in the basin I reviewed the available records of hog farms in the DENR Region III and divided them into four five-year periods. The following are the characteristics of the waste management of the farms as organized from the records: From 1974 to 1979 the number of animals varied from a high 4650 per enterprise with an average of 2556. Half of the farms with records in this period discharged untreated wastewater into the creek or vacant lots adjoining their farms via earthen canals. By the middle of this period, producers began to use settling lagoons, ponds or single or multiple tanks (anaerobic lagoons), to control pollution. From 1980 to 1984, there were still farms without treatment facilities. Septic tanks and settling lagoons were still being used. An intricate waste treatment methodology began to emerge, e.g., two settling tanks connected to anaerobic, facultative and maturation ponds. However, a number of facilities were bypassed. Bio-gas digesters appeared in this period when large farms (up to 10,000 head) were established. The average size of farms remained relatively constant (2554 head/enterprise) due to the proliferation of small farms. The use of complex waste treatment facilities e.g., sump tanks, with multiple slurry tanks, multiple digester tanks, gas-holding tanks, anaerobic ponds, facultative ponds, and polishing ponds appeared between 1985 to 1989. Fish farming began to be integrated with waste treatment as polishing ponds were used to grow tilapia. Bio-digesters, still in use during this time, were connected to several tanks. Sludge tanks, anaerobic ponds and sedimentation tanks in series have appeared but still by-pass canals have been found in some waste treatment facilities, indicating that these were just placed there for the purpose of inspection and not really to treat waste. Direct discharge to river was still prevalent, and the average number of animals per enterprise continues to increase (3043 per enterprise). 131 Over the last few years (1990 to 1994) the state of animal waste management in the region has been characterized by the use of earthen lagoons in combination with settling tanks. Presettling tanks (anaerobic and facultative) and polishing lagoons are now commonly adopted. However, bio-gas digesters have been largely abandoned, except for the largest farms where it is combined with slurry tanks and decantation tanks, settling basins, dilution ponds, and aging ponds. The number of animals per enterprise has remained the same as compared to the 1985-1989 interval, even though there have been increases in the maximum capacities. This was due to the increase in establishment of small farms. The problem at present is that farms are disposing of wastes directly to the river, and for those with waste treatment facilities, the waste has been in excess of the capacity of the facilities. Wastewater treatment facilities (WTF) Many pollution problems arising from hog farms are avoidable through better management practices and by using the technology of waste treatment facilities. The different WTFs described in the inspection reports of the DENR were divided into four groups, from the elaborate series of treatment tanks (group A) to that which only has one earthen lagoon before water is discharged to the streams (group D). Although several water quality parameters were measured, only three were applicable to this study. A calculation of the efficiencies of the four groups are presented in Table 6-2. While the grouping was based on the complexity of the WTFs, the means of the groups failed to show significant (P<0.05) differences in all the three water quality parameters. This suggests that there is reason to believe that the WTFs are not very efficient, most probably because of the large numbers of animals or that the WTFs were not always in use. The high pH values of the effluent may explain some of the variation in the pH of streams where hog farms are 132 concentrated. Assessing nitrogen contribution from BOD would indicate that there may be rationale to assume that hog farms are major sources of nitrates enter the streams. This is in addition to the fact that there were numerous farms that disposed the wastes directly to streams. Table 6-2. Efficiency of wastewater treatment facilities of animal farms as measured by three water quality parameters* WTF pH BOD (mg/1) TDS (PPM) In Out Diff In Out % Eff. In Out % Eff. A 7.11 7.70 0.19 550 79 83 728 176 63 B 6.80 7.45 0.65 355 44 74 242 153 49 C 7.13 7.68 0.55 285 97 68 395 484 64 D 7.54 7.71 0.17 176 20 86 77 39 49 Ave. 7.09 7.62 0.53 420 62 80 495 170 58 In=influent; Out=effluent; Diff = difference; and %Eff.= efficiency (%) of treatment 6.4 Land-use Activities and Water quality interactions: The case of human population There is concern that the human population is a major source of pollution in the basin. This concern is therefore addressed in this section. The barangay centroid of population was used as the geographical location of data on human population, determined on the 1:50,000 topographic map. The role of food manufacturing is not discussed, due to lack of data. However, since it is considered a cottage industry in the basin, and since these types of polluters are located in population centres, they are incorporated in the population pollution index. Results show that human population density has a very weak correlation with nitrate-N concentration, (Figure 6-23), and it is not correlated at all with other water quality parameters. Figure 6-23 illustrates that human population density was only correlated with nitrate-N concentration in stream waters. This weak correlation occurred only during the rising limb of the Figure 6-24. Distribution of 1990 human population in the Pampanga River Basin 133 N o . o T P e o p l e p e r B a r a n g a y i n I S S O < 1 0 0 0 1 0 0 1 - 2 0 0 0 2 0 0 1 - 5 0 0 0 1 0 0 1 0 > 5 0 0 0 B a s i n B o u n d a r y M a i n R o a d s 2 0 3 0 K m N 134 high flow periods and takes place only in the large areas from 250 metre buffer area along all streams up to the total catchment area. This may be explained by the fact that not all highly populated areas are near the streams, as illustrated in Figure 6-24. Another explanation is that during the rising limb of the high flow, the rainfall might have washed into the streams wastes from populated areas that might have accumulated during the low flow period. The weak correlation of human population and nitrate-N in streams may also result from the fact that most human wastes enter into septic systems through the latrines, where the likelihood of the waste entering the streams is less. However, during the rainy season, most of these latrines overflow and may then be washed into the streams. Figure 6-23. Changes in nitrate-N concentration of the Pampanga River during the Rising Limb of the High Flow Period relative to the cumulative human population density in the 500 m buffer zone along major streams 300 er IB 250 \ 200 8. 150 o 100 Q. 50 0 1 person/sq.km. -mean no3 8 11 headwater 16 18 28 44 mainstem stations 53 56 57 mouth 0.80 0.60 01 0.40 £ c E Q . 0.20 °" 0.00 135 6.5 Land-use and water quality interactions: General relationships This chapter demonstrates the influence of flow periods on water quality conditions. The high flow periods always had better correlation with land-uses than the low flow periods. The suggested explanation of these differences in performance in the different periods is the effect of the dilution of rainfall and the dominance of groundwater during low flow. Results with the buffer analyses suggests that a subset of the total basin area (buffer zone) may be used in the study, and provide more accurate predictions. For example, it was observed that using a minimum of a 500 metre buffer zone on all streams could give results similar to those using the total area. There are exceptions, such as the case of nitrate-N, where the best correlations in all flow periods took place at the 500 metre buffer zone along major streams. This argues that the importance of the land-use analysis in this buffer area is of greater value in explaining the variations in nitrate-N concentration than the total area, and therefore land-use management to reduce nitrate-N in streams has to be directed to this area. Of the five parameters analyzed against land-uses, variations in TDS and COD were almost totally explained by variations in lahar-covered areas, while variations in ortho-phosphate concentrations were mostly explained by variations in lahar-covered areas and settlements. Variations in pH may be explained by variations in all of the land-uses. A general inference of this study is that different species of animals in different area classifications affect the water quality of the streams during different flow periods. It is also clear that among the five water quality parameters studied, variation in the nitrate-N originate from point sources, while animal production and human population are the non-point sources. Nitrate-N had a weak correlation with land-use cover alone. In combination with effects of animal and human populations however, strong relationships resulted, supporting the argument that factors such as point sources of pollution may be exerting an additional effect on the nitrate-N. Table 6-3 summarizes the regression analysis of nitrate-N and the combination of land-use cover and land-use activities, in the 500 m buffer zone along major streams. Although all the equations presented are statistically significant (P<0.05), it can be observed that the mainstem stations have very high multiple regression coefficients, while in the tributaries, a high regression coefficient appears only during the rising limb of the high flow period. It is during this flow period that the nitrogen from runoff may eventually influence the nitrate-N concentration of streams. Since this potential nitrogen is important, the next chapter will present a framework for calculating it, including management implications. Table 6-3. Regression equations between nitrate-N and land-use cover and activities Type of station/ multiple SE Equation flow period R Mainstem Falling Limb .97 .13 16.776695 + .352059A - 12.770108G - .004079H-4.060808R - 91.353144S - 44.790492W Low Flow .97 .08 0.659017 - .021699A + 8.810262G + .001173 + 2.040521R-15.230816S -16.639211W Rising Limb .95 .14 -2.667760 +.093081A - 2.816017G - .001527H + 4.494218R-7.848413S + 13.849755W Tributaries Falling Limb .45 .47 -0.636159 + .000805A + 1.862778G - .000717H + 1.572151R + 6.205724S + 1.30707045W LowFlow .54 .27 -.142592 - .004158A + 1.148717G- .000381H +.884223R + 2.766269S +.852684W Rising Limb .81 .15 -.527370 + .000685A+.67918G+.000009H + .780501R + .798840S +2.307625W where A=AUE/sqkm; G=%grassland; H=persons/sqkm; R= % Rice; S=% settlement; W=%woodland 137 Chapter 7. NITROGEN BUDGET : A FRAMEWORK FOR ASSESSING NITROGEN M A N A G E M E N T IN T H E P A M P A N G A RIVER B A S I N The focus of this chapter is on the management of nitrate-N on the land through the use of a nitrogen budget analysis. This is an interesting way to compare land-use and water quality interactions. To address the concern of nitrate contamination in both surface water and ground water, it was necessary to identify the major contributors to fluxes of nitrogen in the basin. Although nitrogen sources may be evaluated in several ways, a nitrogen budget was employed, showing average annual inputs and sinks. When calculating average nitrogen accumulation, it was possible to identify areas where surplus applications were highest (hotspots). The preparation and analysis of the nitrogen budget identified various problems associated with the accumulation of nitrate-N in the basin, and pointed towards animal manure and fertilizers as important factors for management. This chapter shows clearly the relationship between land-use and water quality in the basin. 7.1 The nitrogen budget The nitrogen cycle from which the nitrogen model presented in Figure 7-1 was developed, can be thought of as pools of nitrogen in a number of compartments within the biosphere and of exchanges of nitrogen among the compartments. The exchanges are controlled by rates of biological and chemical reactions and by hydrological transport. Although as a cycle, the amount of nitrogen in each compartment should be fairly stable, nitrogen may accumulate temporarily in various compartments because of differences in rates of the many reactions involved. It is however with the surface water compartment and the run-off transport that the ultimate goal of this nitrogen model is concerned, and therefore the procedure followed here is tailored to the attainment of this goal. 138 Atmosphere volatilization atmospheric deposition & fixation Crops 1 uptake Surface Water run-off Fertilizers denitrification Land Surface Human Waste Animal Manure leaching Ground Water Figure 7-1. Simplified Nitrogen Model The precipitation data used in the study were manually copied from the hourly log of the telemetering stations of the Philippine Atmospheric Geophysical Astronomical and Seismologic Authority (PAGASA) from August 1993 to July 1994. Since not all the catchments had rain gauges, the rainfall record of the telemetring station nearest the centroid of the catchment was used as its own precipitation record. The total daily precipitation was calculated out of the daily logs. The evapo-transpiration values used in the study are presented in Table 7-1. The evapo-transpiration values were deducted from the precipitation values to yield the effective precipitation, which was the basis for the calculation of runoff and its nitrate-nitrogen concentration. 139 Table 7-1. Computed 10 days evapo-transpiration data for Pampanga (LREP, 1986) M O N T H M O N T H L Y A V E R A G E (% of precipitation) January 40.00 February 45.33 March 61.00 April 63.00 May 63.33 June 47.00 July 48.67 August 33.33 September 43.00 October 40.33 November 40.00 December 40.00 7.1.1 Sources of nitrogen Animal manure The 1990 animal population provided by the Bureau of Agricultural Statistics (BAS) was used to estimate the animal manure produced in the basin. The factors used to measure the total nitrogen production from the manure are presented in Table 7-2. Since categories for buffaloes and goats were missing, values for cattle were used for buffaloes, and based on the A U E factor mentioned in the preceding chapter, dividing the values for cattle by four generated values for sheep and goat. Table 7-2. Conversion factors used in estimating nitrogen outputs of animals* Animal Approx. Weight Total N/day dry solids/day chicken 4-5 lb. 0.0036 lb. 0.066 lb. swine 100 lb. 0.0640 lb. 0.970 lb. cattle 1000 lb. 0.2600 lb. 9.000 lb. ducks 4-5 lb. 0.0080 lb. 0.160 lb. * Source: Straub (1990) 140 Human waste To estimate the contribution of nitrogen from human wastes, the factors presented by Straub (1990) were used. These include assumptions that 35-70 grams of dry feces and 50-70 grams of dry solids in urine are produced by an adult individual in one day. Other assumptions were that 5-7 % of the feces (containing 66-80 % moisture) and 15-19% of the urine (containing 93-96% moisture), is nitrogen. The averages of the ranges were used in the study and the resulting factor was multiplied to the projected 1993 human population for each catchment. Sewage systems do not exist in the basin, but most of the households are served by latrines provided with septic tanks. The National Census and Statistics Office (NCSO) included in their survey of 1990 the percentages of households in different categories of waste disposal systems for each municipality. The categories they used were aggregated into two groups for the purpose of this study; those provided with septic systems and those without any structural control of waste. The latter was then called the waste that is spread on land since such waste would be found scattered on land. Through use of the GIS technique, an overlay of the catchment areas, the municipalities (with data on waste disposal), and the barangays (with data on population) provided the required information for dividing the human waste into the two categories for each catchment. Food processing wastes would be expected to contain significant quantities of nitrogen. Unfortunately, there is no record of food processing industries to use as a basis for estimating its contribution. Hence it was not included in the calculation, although it is recognized that nitrogen in food processing wastes may constitute a significant point source about which little is known. 141 Commercial fertilizers Commercial fertilizers are thought to be a main source of nutrients enriching the Pampanga River Basin. Tables 7-3 and 7-4 show that there was a considerable increase in application of commercial nitrogen fertilizer in the basin, and there is some concern regarding its influence on water quality. The PHILRICE Rice Household Survey of July 1993 was the basis for the level of nitrogen fertilizer application used in this section of the study. The average rates of nitrogen application were 85 kg-N/ha for the wet season and 101 kg-N/ha for the dry season. A GIS overlay of the Nueva Ecija Area land-use map and elevation map reveals that most of the irrigated fields are at or below the 50 metre elevation. Since the 1993 land-use map of the whole basin does not indicate the location of irrigated fields, in dividing all the rice fields into rain-fed and irrigated, all rice fields having lower than or equal to 50 metres in elevation have therefore been designated as irrigated rice fields. The irrigated rice fields have continuous cropping systems, but two croppings of rice per year was used in the calculation of fertilizer input. For the rain-fed rice fields, the once a year planting was used. Table 7-3. Wet season fertilizer application in five different years in the basin, in percentage of farmers Range of total fertilizer application (kgN/ha) 1978* 1979* Y E A R 1980* 1981* 1993** over 100 17 18 13 18 40 81 -100 13 15 19 18 22 6 1 - 8 0 17 28 24 31 19 4 1 - 6 0 21 15 29 25 13 2 1 - 4 0 17 17 13 7 3 1 -20 14 3 1 1 2 0 1 4 1 0 1 Average kg N/ha 61 63 67 72 102 •Source: NIA (1978,1979,1980,1981) **PHILRICE (1993) 142 Table 7-4. Dry season fertilizer application in five different years in the basin, in percentage of farmers Range of total fertilizer application (kgN/ha) 1978* 1979* Y E A R 1980* 1981* 1993** over 100 31 54 51 62 59 81 - 100 20 20 17 16 11 61 - 80 14 12 18 16 15 4 1 - 6 0 14 8 5 4 5 2 1 - 4 0 15 6 5 1 6 1 -20 4 0 0 1 2 0 2 0 4 0 2 Average kg N/ha 84 102 102 114 113 •Source: NIA (1978,1979,1980,1981) **PHTLRICE (1993) Atmospheric deposition Since precipitation chemistry data in the country are lacking, the 1.1 mg/1 of combined N 0 3 - N and N H 4 -N in rainfall estimated for B.C. (Ministry of Environment and Parks, 1988) was used. This value was only for wet deposition and in including dry deposition, this value is usually multiplied by a factor of two. However in the present study, it was assumed that the total deposition was 1.1 mg/1. The accuracy of this value for use in the Philippines does not present a problem since a comparison of the catchments is of more importance, and the value is assumed to be uniform throughout the watershed. The daily rainfall data from P A G A S A of 11 telemetering rain gauges distributed throughout the basin was used to obtain the one year of effective precipitation (August 1993 to July, 1994) from which the atmospheric deposition of nitrogen is based. 143 Biological fixation A considerable amount of N 2 is fixed symbiotically by cultivated legumes as well as from non-symbiotic fixation. Since there are no records for the latter types of nitrogen fixers, only the legumes among the plants are considered here. The only data source for legume production are the four reports on Land and Resource Evaluation Projects (LREP, 1986 and LREP, 1988), one for each of the four provinces that make up the basin. In the reports, areas planted to paddy rice and the legumes were reported. Ratios of rice fields to areas planted to legumes were calculated to have a range between 1:0.0015 and 1:0.0300. The average ratio of 1:0.013 was used in this study. The computed areas were multiplied with the conversion factor for fixing atmospheric nitrogen by symbiotic fixation of 150 kg/ha-year as reported by Schepers and Fox (1989). Non-symbiotic fixation as well as fixation by leguminous trees are assumed not to influence the nitrogen in the water and were therefore not included in the calculation. Soil mineralization The annual mineralization rate used in the study came from that used by Meisinger and Randall (1991). A value of 1 % was used on the soil up to one third of a metre depth from the surface. From two field experiments conducted in the basin during 1985 to 1986 by De Datta et al, (1988) the total N content in the soils ranged between 0.4 - 1.0 g N/kg soil. The average value of 0.7 was used in the study. The LREPs (1988) provided the average bulk density of soil at 1.15 gm/cc. 144 7.1.2 Sinks of nitrogen Crop uptake Since rice is the major crop grown in the basin, the crop uptake estimate was based solely on rice. The International Fertilizer Development Centre (1978) reported the apparent recovery of N fertilizer in rice as low as 15 % and to as high as 62 %, with the average range between 30-40 %. Cassman et al, (1993) in a recent study of 44 farmers' fields in Central Luzon, found the mean N uptake efficiency from fertilizer to be only 36%. However, the same researcher concluded that in field experiments, flooded rice generally recovers 20-40% of applied N, compared to upland crops which normally recover about 40-60%. Furthermore, it was found that dry season crops average 10-15 % better recovery than the wet season crops. For this study therefore the lower value (30%) was used for wet season rice, while the higher value (40%) was used for the dry season rice. Although the N cycle in rice soils is very complex, it is well known that the poor utilization of N fertilizer by rice is largely attributed to losses of N from the soil-plant system, loss mechanisms that are peculiar to waterlogged soils and thus accounting for the especially low efficiency of N for rice compared to other crops (IFDC, 1978). The intermittent flooding of soils promotes fertilizer losses by allowing nitrification to occur during the drained or aerobic phase, and subsequent denitrification during the waterlogged phase. Volatilization At a farm level Jarvis (1994) mentions that researchers found that the equivalent of 18% of inorganic fertilizer input is lost through volatilization. For animal manure, Dewi (1994) cites researchers who concluded that, depending on the storage conditions, the length of storage, and the disturbance the manure is given, from 10-80% of the nitrogen from manure is volatilized. A 145 conservative 10% was used in the study for the fertilizers, the animal manure, and the human waste component that does not go to the septic tanks. Denitrification Based on the data presented by Meisinger and Randall (1991), it was assumed that 10% of the inorganic N coming from fertilizer and rainfall is lost by denitrification. For manure, it was assumed that 22% of the net manure input is subject to denitrification on grasslands (Jarvis 1994). The latter author, citing several researchers, showed that greater levels of denitrification occurred in soil where readily decomposable carbon had been added to the soil, such as where a crop had been grown or animal manure had been added, and the greater denitrification in fallow soil was due to the increase in readily available energy supply for microorganisms to carry out denitrification. In the study, 10% was used as the denitrification rate on all nitrogen inputs. 7.1.3 Environmental Nitrogen Environmental nitrogen is used here as that portion of the nitrogen in the environment which is available for polluting the soil, groundwater and surface water. Inputs of nitrogen into the system from all sources were added, resulting in the overall total nitrogen present on land. Likewise, all sinks of nitrogen were added. Subtracting the sinks from the inputs yielded the total available nitrogen for leaching or run-off, termed here as environmental nitrogen. From this total was calculated the proportion that was leached to the groundwater, and the proportion that was available for run-off. 146 Leaching Inching is the physical process of the downward movement of dissolved constituents in soil solution. Leaching losses from 3.4 to 25.4 % from rice fields in the basin have been reported by IFDC (1978). Since the texture of the soil is an important factor in leaching, the soil textures found in the basin were divided proportionately into a leaching range. Results are presented in Table 7-5. The leaching loss rate for each catchment was obtained by GIS overlay of the catchment area with the soil texture layer. The resulting rate for each catchment was multiplied by the environmental nitrogen to give the amount of nitrogen leaching to ground water. Table 7-5. Soil texture and assigned leaching loss* soil texture leaching loss (%) sandy 25.40 sandy loam 21.88 fine sandy loam 18.60 loam 15.73 silt loam 13.16 silt 10.89 clay loam 8.86 sandy clay loam 7.20 silty clay loam 5.84 sandy clay 4.78 silty clay 4.01 clay 3.40 *Leaching loss range of 3.4% to 25.4% (IFDC, 1978) Run-off and expected total nitrogen concentration in run-off The remaining environmental nitrogen, after subtracting that portion leaching to the groundwater, is the total available nitrogen for run-off. To estimate an expected total nitrogen concentration in run-off, the run-off volume was determined by using a run-off coefficient based on the average slope of the catchment. The run-off coefficients supplied by Black (1990) were used 147 and are presented in Table 7-6. Through GIS overlay of the catchment map and the slope layer (derived from the elevation map), the average slope and therefore the run-off coefficient for each catchment was obtained. These were multiplied by the corresponding volume of effective rainfall for each catchment and the expected total nitrogen concentration was then calculated. Table 7-6. Run-off coefficients attributed to different slopes (values taken from Black, 1990) Slope Description Run-off Coefficient. <18 % Flat, rolling farmland 0.333 18-25 % Moderate, uneven terrain 0.500 > 25 % Steep, rough hilly country 0.667 7.2 Nitrogen management in the basin 7.2.1 The present condition The nitrogen budgets for individual catchment is found in Appendix Table 7-1 a. The nitrogen budget for the whole basin presented in Table 7-7 reveals that animal manure contributes more than half, and inorganic fertilizer almost a quarter, of the total nitrogen into the basin. These two sources of nitrogen therefore are very important. If something is to be done to address the nitrogen problem in the basin, these two sources should be targeted. Table 7-7 also reveals that crop uptake, which should be the major sink of nitrogen, accounts for a little more than 40 percent of the total sink in the basin. The explanation here is the fact that rice, the major crop, has a very poor efficiency of nitrogen utilization as compared to other crops, which is further aggravated by poor timing of fertilizer application. The fertilizer applied to rice is almost totally inorganic, although technologies to use animal manure are being developed. With a large pool of nitrogen present in unutilized animal manure, the environmental 148 nitrogen on the land surface accounts for more than a fifth of the total nitrogen input, and since only approximately 2% is leached to the groundwater, an appreciable amount of nitrogen ends up in the surface water. Table 7-7. Cumulative nitrogen fluxes in the Pampanga River Basin as determined at Station 57 (Sulipan, Apalit). Each catchment has its own computation as presented in Appendix Table 7-la ...?.0JS.^5..°?.Nitr96^!! ,..Qy.^ .^.ft9!!E?.?/X?a.r). Percent Animal manure Inorganic fertilizer Human input Septic system Non-septic (land spread) Atmospheric deposition Biological fixation Soil mineralization 124128 58069 4946 4748 29198 1093 19591 51.3 % 24.0 % 2.0 % 2.0 % 12.1 % 0.5 % 8.1 % Total Sinks of nitrogen Crop uptake Volatilization Denitrification 241773 77393 72965 42162 100 % 40.2 % 37.9 % 21.9% Total 192520 100 % Nitrogen on land surface Nitrogen leached to groundwater Nitrogen available for run-off 49252 4588 44665 20.4 % * 1.9 %* 18.5 %* * as percentage of total nitrogen inputs The average expected total nitrogen concentration in the run-off in each catchment was only 23 ppm. Figure 7-2 shows the spatial distribution of the total nitrogen concentration that is expected in each catchment. The stations were divided into four groups (green, yellow, red, black) 149 F i g u r e 7-2. D i s t r i b u t i o n o f e x p e c t e d to ta l n i t r o g e n c o n c e n t r a t i o n in runo f f o f the d i f fe rent c a t c h m e n t s i n the P a m p a n g a R i v e r B a s i n . 150 based on the expected values. As illustrated, those on the eastern portions of the basin exhibited the lowest expected values, which is most probably explained by the fact that these catchments, aside from having low animal and human population densities, also receive the highest amounts of rainfall in the basin. These catchments are found in the hills and mountains of the basin. The stations with expected values from 10 to 20 ppm share the characteristic of predominantly sloping grassland-rice field areas, while those belonging to the next upper group have higher animal and human populations with catchments predominantly under rice cultivation with level terrain. The hotspots, or the group with the highest expected values consist of catchments with large settlement areas such as the town of Baliuag at Station 57, or with a very high animal population such as at Station 49, or a combination of both such as in the urban areas of Cabanatuan City and the town of Talavera for Station 11, or the towns of Bamban and Concepcion at Station 43. Table 7-8 presents the factors affecting the expected value which registered significant differences in means among the four groups of stations. The difference between group 1 and 2 is the significantly (p<0.05) higher amount of animal manure of catchments in the latter group. The differences between group 3 and 4 are the significantly (p<0.05) higher values of all the factors for group 4. The importance of animal and human population in the expected value of total nitrogen is supported by the fact that only these two factors gave significant (p<0.05) correlations (R2 = 0.80 for animal manure and R 2 = 0.33 for human waste spread on land) with the expected total nitrogen values. It is therefore wise to direct attention to the animal waste in any nitrogen management in the basin. Two scenarios dealing with these two factors were studied and results are discussed. 151 Table 7-8. Factors affecting expected total nitrogen value*** Group Animal Fertilizer Human waste* Crop Manure* Appl* Uptake** Category Expected N range (ppm) % % % % 1 <10 28.9 a 14.4 a 1.1 a 28.7 a 2 10-20 37.2 b 17.7 a 1.9 a 29.7 a 3 21-30 52.6 c 28.7 b 2.1 a 42.7 b 4 >30 70.7 d 36.3 c 2.8 b 48.3 c ***means in the same column followed by the same letter are not significantly different at (P<0.05) ** % of the total nitrogen sink * % of the total nitrogen input An analysis on the expected values of total nitrogen (ETN) in the runoff against the observed nitrate-nitrogen (ONN) concentration in the streams for each catchment, revealed significant (p<0.05) correlation, with R 2 = 0.38. The relationship between E T N and ONN varies from catchment to catchment, and this may be due to the inherent differences in the catchments, especially with regard to the differences in proportions of the different land-uses. This suggests that aside from land-use, other factors may also be important in the eventual translation of the E T N to the ONN concentrations in streams. 7.2.2 Scenario 1: Increasing animal production As mentioned in Chapter 4, to counteract the dwindling rice production in the region, animal farming was promoted to improve or maintain the overall agricultural production. The government has planned for this increase in the basin, as indicated by the planned slaughterhouses in Palayan City and General Tinio (Zalun, 1994: Personal Communication). To determine the 152 effect of this plan on the nitrate concentration of the streams in the basin, the nitrogen budget framework was developed and experimented. The effect of increasing animal manure production at four different levels, on the nitrate nitrogen concentration in streams, termed here as predicted nitrate-nitrogen (PNN) was studied as the first scenario. PNN was calculated for each catchment based on the relationship of E T N and ONN. As illustrated in Figure 7-3, even with a three-fold increase in animal production, only one station would exceed the limit of 10 ppm. However, it must be noted that this is in isolation of the possible decreases in crop uptake, which may be due to decreases in agricultural land. 7.2.3 Scenario No. 2 :Decreasing areas under rice cultivation Figure 7-4 illustrates the predicted changes in nitrate-N concentration of streams when four levels of agricultural land expansion were used. As can be observed, the general trend is for the predicted nitrate values to decrease as more agricultural land is lost, a trend which could be attributed to the decreasing total amount of nitrogen fertilizer applied in each catchment. The low efficiency of rice to use nitrogen causes the total crop uptake to be less than the decrease in fertilizer addition. However, more than a third of the catchments had an initial increase in the predicted nitrate values at the agricultural land level which is 5% less than the actual area. This proves once again that the rice fields intercept the runoff and the nitrogen, so when the size of rice fields decrease, the amount of nitrogen intercepted would be lower, hence a higher overall nitrate in streams. This effect however is limited when the loss of agricultural land is 5% or less. 155 7.3 Improving nitrogen management in the basin As discussed above, the increasing animal production in the basin would be the greatest reason for attempting to improve nitrogen management in the basin. Producing rice which is the staple food, however is more important economically and politically. One way to combine the goals of increasing productivity through intensive rice production, increasing animal production, and still managing to limit pollution of the streams in the basin is through proper nitrogen management. The best management practice for controlling nitrate accumulation in the streams is the management of nitrogen and water inputs on the farms. If the animal manure can be used properly and extensively in rice production, then, it would limit the loss of nitrogen into the atmosphere or groundwater, while at the same time increasing the sink through crop uptake, thereby decreasing nitrogen in runoff. This would also be economically beneficial to farmers, where inorganic fertilizers are very expensive. The problem with using animal manure as fertilizer is with the convenience and timing of application. Some managers of animal farms who were interviewed protested that the rice growers use the wastewater from these farms for irrigation during the dry season, but find it an inconvenience during times when water is abundant. With co-operation between the two sides to dispose of and use the wastewater, not only would some economic problems be solved, but so would many social issues. Although the farmers are now using a split application of inorganic fertilizers for better efficiency, they still need information on the best strategy for management of manures as fertilizers. When the application of fertilizer fits the demand of the crop, savings in both economic and environmental costs would be achieved. Chapter 8. ENVIRONMENTAL PERCEPTIONS OF BARANGAY CAPTAINS: IMPLICATIONS FOR F U T U R E OF L A N D - U S E AND W A T E R Q U A L I T Y IN T H E P A M P A N G A R I V E R BASIN The Philippine government has adopted a policy to enlist the support of the barangay (village) officials in the government's campaign against pollution and other environmental problems (Feliciano et al, 1992). Since local conditions vary, it was believed that it is better left to local governments to formulate rules and regulate activities undertaken within their territorial limits. Pursuant to this policy, the President issued PD No. 1160 vesting authority in barangay captains (barangay councilman and barangay zone chairman) to enforce pollution control and other environmental regulations. With Republic Act No. 2264, the local autonomy act, there is optimism that enforcement and implementation of the countless regulations will take place. In addition to the barangay's potential role in the environmental management, its role in sustainable development has also been recognized. This latter role was emphasized in the latest development plans of the N E D A (RDC, 1992), especially in terms of more specific project identification and implementation. There was even a plan for the establishment of an Integrated Barangay Development Councils as the counterpart of the provincial and municipal development councils in the barangay to be organized and trained to assume greater responsibility in local development activities. This chapter presents the environmental perceptions of the leaders in the barangay and the realities in their localities to determine the opportunities and problems for involving the barangay into environmental management, specifically the management of land-use and water resources in the basin. A total of 172 barangay captains (village chiefs), participated in the survey and answered questionnaires identical to the one presented in Appendix 2-4a. Figure 8-1 illustrates the distribution of the respondents in the study area. 157 Figure 8-1. Distribution of Barangay Captains Who Answered Questionnaires 158 8.1 Background Information on the Respondents In order to put the perceptions of the barangay captains into perspective, some background information was gathered. This included personal data such as age and the number of years they have been in the community, in order to determine historical reliability of their answers. 8.1.1 Personal Data Age and Years in Residence The barangay captains know their communities well enough as revealed in Table 8-1. The majority of them are more than 40 years in age and have been staying in their respective localities for more than 30 years. Since the survey was carried out before the barangay elections in 1994, it is presumed that most of the incumbent leaders have been in their post for at least one term which is six years, and therefore were very qualified to address questions that were posed to them. Table 8-1. Frequency distribution of age and residence of respondents, in years (N=172) Years Number of respondents with Number of respondents residing in the corresponding age barangay for the duration >70 3 1 61 - 70 26 17 51 -60 23 18 41 -50 36 25 3 1 - 4 0 12 18 <30 - 21 159 Occupation and educational attainment Table 8-2 reflects the fact that this is an agricultural area and that the majority of the respondents are farmers with an elementary to high school education. No attempt was made to analyze the survey results in terms of occupation or education since not all categories of each variable were represented. Table 8-2. Occupation and educational attainment of respondents, in percentage (N = 146) Occupation Educational Attainment Total College High School Elementary Farming 8 42 29 79 Business 5 1 1 7 Housekeeping/Pensioner 2 1 2 5 Others (Driving, Clerk, 3 5 1 9 Hair-cutting, Carpentry) Total 18 49 33 100 Personal concern for the environment To capture the perception of the respondents on environment-related problems, their concern for the environment should first be established. When asked to rate themselves on a five-point hedonic scale, it was revealed that three quarters of the respondents rated themselves as very concerned with environmental problems and that nearly all the respondents were concerned (see Table 8-3). Table 8- 3. Respondents' self-evaluation on environmental concern (N=150) Level of concern Percentage Very concerned 75 Somewhat concerned 21 A little concerned 2 Not at all concerned 1 Do not know 1 160 8.1.2 Personal knowledge of the evaluated stream Familiarity and Awareness to the Evaluated Stream The respondent's familiarity with the stream was evaluated by asking two related questions- a self-evaluation of the degree of familiarity with the stream using a five-point hedonic question ranging from very familiar to don't even know it's there, and whether or not they are aware of the local streams in their village. Table 8-4 shows that all the respondents were familiar with the stream. More than two-thirds of the respondents were very familiar, but a quarter of them were unaware of the stream during their common trips, explaining the non-significant (p<0.05) relationship between the two variables. These results therefore gives a caution to the interpretation of and confidence that must be given to, the opinion of the respondents regarding the characteristics of the streams. However, later sections of this chapter would reveal that the respondents' knowledge of the stream may also have come from the people in the community who are really aware and familiar with the streams, as the respondents are the first line of complaints. Table 8-4. Respondent familiarity with and awareness to the evaluated stream, in % (N = 159) Familiarity Aware Not Aware Total Very Familiar 54 16 70 Familiar 20 9 29 Just Know it's there 1 0 1 Total 75 25 100 The familiarity on barangay boundaries was another way of appraising the knowledge of the respondents regarding their environment. The frequency distribution presented in Table 8-5 resembles that of the respondents' familiarity with the stream. This indicates further that the 161 respondents believed they were familiar enough to give a valid opinion on matters affecting their barangay. Table 8-5. Respondent familiarity with barangay boundary, in percentage (N = 169) Familiarity Percentage Very familiar 74 Familiar 14 Fairly familiar 4 Not familiar 1 Don't know 7 Distance of Respondent's Residence from Stream Two questions were asked, one relating to distance in kilometers, and another by description, when the respondent's were requested to locate their residence in relation to the streams they were evaluating. Results displayed in Table 8-6 revealed that more than 85 % of the respondents live within a kilometer from the stream, or within a five-minute walk from the stream. The statistical relationship between the two questions was highly significant (p<0.01). The data indicate that most of the respondents actually can easily walk to the stream but are not actually right next to it. Table 8-6. Distance of respondents from streams, in percentages (N=163) Distance in km Respondents Distance by description Respondents < 1 km 8 5 % Right next to the stream 6 % Has view of the stream 28 % Within a five-minute walk 55 % 2-3 km 11 % Farther than a five-4-5 km 2 % minute walk to the stream 11% 6-10 km 1 % > 10 km 1 % Total 100 % 100 % 162 8.2 Perceptions on Environmental Problems 8.2.1 General Environmental Problems Community Problems The importance of the environment relative to other problems in the community can be gauged from the ranking of five community problems by respondents. Results presented in Table 8-7 were expected. The respondents believed that the most pressing problem in their communities is economic in origin, health and environmental problems come next, while shelter and peace/order came last. Table 8-7. Respondents' ranking of five major problems (5=most pressing to l=least pressing)* Point Peace and Order Environment Economy Health Shelter f f f f f 58 34 3 26 41 11 21 14 30 18 16 13 24 17 16 4 19 13 21 7 7 10 69 5 11 179 241 500 246 208 ( 5 ) ( 3 ) 1 2 3 4 5 Total points *Total points were calculated by multiplying the point by the frequency in each category, followed by adding all the points Environmental Problems The major environmental problems in the basin as reflected by the answers of the respondents are presented in Table 8-8. It can be observed that deforestation is perceived to be the most pressing problem. This is no surprise since the government and media are very aggressive in campaigning against deforestation. 163 Table 8-8. Respondents' ranking of environmental problems in their own barangays (5=most pressing problem to l=least pressing problem)* Point land conversion groundwater pollution air pollution stream pollution deforestation f f f f f 1 39 30 36 29 19 2 18 15 15 17 9 3 8 11 8 7 10 4 8 11 10 10 7 5 26 14 6 16 39 Total Point 261 207 160 204 290 (Rank) ( 2 ) ( 3 ) ( 5 ) ( 4 ) (1) *TotaI points were calculated by multiplying the point by the frequency in each category, followed by adding all the points The land-use perception of the barangay captains did not agree with the data discussed in Chapter 3. When they were asked to rank five environmental problems in the basin, the most pressing problem they perceived was deforestation first before the conversion of agricultural land. In Chapter 3, deforestation was shown to have occurred largely from 1953 to 1980 but there has been an increase from that year on to 1993. This illustrates how people's perception has not changed with time. It makes one wonder whether deforestation would always be perceived as a problem no matter what reforestation projects are undertaken. It might even be argued here that this perception is reflected in the fact that there were numerous reforestation projects but none for land-use management. 164 8.2.2 Perceptions on stream Pollution Attractiveness and Use of the Streams In terms of attractiveness, Table 8-9 shows that only a few streams were considered unattractive by the respondents. Those who were aware of the streams on their common trips and those who were more familiar with the streams were more inclined to find the stream more attractive than those who do not, as indicated by the statistically significant relationships of attractiveness on both awareness (p<0.05) and familiarity (p<0.01). Table 8-9. Respondent's opinion on the attractiveness of streams (N=171) Rating Percentage Very attractive 24 Somewhat attractive 30 Neither attractive nor unattractive 39 Somewhat unattractive 6 Very unattractive 1 To confirm the ratings mentioned above, questions were asked regarding the recreational and other uses of the streams. The potential and the actual uses are compared in Table 8-10. The regard for economic use over the recreational use of the streams is obvious, as irrigation and fishing obtained higher points than the rest. The potential and actual uses were very similar. In fact, statistical correlation between potential and actual uses were all highly significant (p<0.05). Table 8-10. Respondent's opinion on potential and actual uses of the streams, in percentage (N=172) Type of use .?.9.t?n.fiaJ Actual Irrigation 45 37 Fishing 31 33 Laundry 15 13 Bathing 0 10 Scenic enjoyment 9 7 Total 100 100 165 Degree and manifestations of stream pollution In terms of stream pollution, the majority (70 %) of the respondents maintained that the streams are just a little polluted or not polluted at all as shown in Table 8-11. Only 7 % reported a definite perception of pollution in their streams. It was interesting to find out that a majority (6/10) of these polluted streams are near the mouth of the river. Table 8-11. Perception of stream pollution by respondents (N=162) Rating Very polluted 7 Somewhat polluted 19 A little polluted 30 Not polluted 40 Don't know 4 The top three manifestations of a stream's pollution as perceived by the respondents are the following: garbage and organic matter; fish kills and poisoned fishes; and the stream's foul odor and unsightly appearance. Similarly, these are also the most common complaints coming from their constituents (Table 8-12). Significant (p<0.05) correlation between the average seasonal nitrate concentration and pollution rating by the respondents was not found. Table 8-12. Noticeable signs of pollution as perceived by respondents vs. usual forms of complaints from constituents, in percentages Type of pollution/complaint Perceived Received (N=116) (N=132) Garbage; solid wastes; dead plants/animals 39 41 Fish Kills; fish diseases; reduced stock; poisoned fishes 13 12 Foul odour; dirty appearance; bubbles 38 33 Human Diseases 1 0 Pesticides/waste-water from industry 6 0 Siltation; lahar; quarrying; erosion 3 14 166 The pollution of local streams was traced back by 38%, 56%, and 6%, of the respondents to less than 10 years, 10-20 years, and over 20 years, respectively. The results indicate that most of the pollution is a recent occurrence- within the last two decades. Pollution that results in fish kills, fish diseases and reduced fish stocks, as well as erosion, and siltation problems, are traced back to only the last decade. Other types of pollution have been observed in the watershed for more than a decade. Another way to determine the severity of pollution is to know whether the pollution has affected the respondents to such an extent that they have considered moving away from the problem. When respondents were asked whether or not they would consider moving from their present location, a majority disclosed that they would prefer to stay (Table 8-13). When the frequency is broken down according to the distance of respondents from the stream, no statistically significant (p<0.05) relationship was established, indicating that those who are closer to the stream were just as prone to moving as those who are farther from the stream. Table 8-13. Willingness to relocate residence (N=168 ) Responses Percentage Stay where they are Move right next to stream Move to a place where they can view the stream Move to a place within a 5-minute walk to stream Move farther away 61 % 2 % 6 % 21 % 10% When asked to comment on the effect of the stream in their willingness to move near or far from it, those who wanted to move closer had the following reasons, in decreasing frequency: dry-season irrigation, fishing, health effects, personal reasons. Those who wanted to live farther from 167 the streams had reasons such as the river overflowing during the rainy season, the effect of lahar, silt and pollutants carried by the river. The majority (72 %) of the respondents believed that the presence of the stream has no effect on the value of their homes, pointing to other more important factors. Those (28 %) who thought otherwise were mostly concerned with the possibility that floodwaters might destroy their homes and therefore the land would be cheaper. A small number of respondents however offered the answer that since water is a useful commodity and that areas near streams are excellent picnic sites, places near them would be more expensive. Perceived sources of stream pollution The respondents were asked to rank four of the most likely causes of stream pollution in their communities. Answers are tabulated in Table 8-14. When the ranks and the frequencies were multiplied and the total points determined, the following trend resulted: farming, animal raising, industry, and deforestation. The trend reflects the agricultural environment of the basin. It is surprising however, that the respondents, a majority of them farmers, thought that their livelihood is the most probable source of pollution. Table 8-14. Evaluation of four probable causes of stream pollution by respondents (5=most probable to l=least probable) Point Rice Farming Industry Deforestation Animal Farms 1 34 18 23 11 2 7 3 6 9 3 8 6 6 13 4 12 6 7 12 5 22 22 10 12 Total points 230 176 131 176 (Rank) ( 1 ) (2.5) ( 4 ) (2.5) 168 8.3 Barangay Captain's competence for pollution control Having determined that the barangay captains have ideas regarding the sources of pollution, this section is devoted to identifying evidence of enforcement of pollution control regulations, if present, as well as evaluating how they have used the code in their drive for pollution control. 8.3.1 Evidence for enforcement In the community, the barangay captain plays a major role in solving pollution problems. This is supported by the answers provided by the respondents when asked what their constituents would do were they able to identify the major polluters (Table 8-15). Table 8-15. Community actions regarding pollution as perceived by respondents (N=164) Responding Answer 22 % They would not do anything 43 % Report to the Barangay Captain Immediately 10 % Organize their neighbors for legal action 13 % Write letters to polluters 12 % Organize or take part in clean-ups As can be observed from the results, most of the respondents believe that their constituents would just report the problem to them or would not do anything about the problem. Organizing for clean ups, rallies or even writing to polluters are just not popular solutions on the part of the constituents. 169 Previous actions on pollution as can be recalled by the respondents are presented in Table 8-16. The figures could mean that there are equal chances for action to correct the problem. For solutions, the people look to the government, while citizen and legal actions are rarities. This lack of action could really be frustrating to those who would like to report complaints, a likely factor in the occasional reporting of complaints (see Table 8-17). Table 8-16. Previous actions on pollution problems Action Percentage No action at all 50 Formal Complaint to captain 30 Action from the government 15 Citizen action (rallies, pickets) 4 File legal action/court cases 1 Table 8-17. Frequency of pollution complaints reported by constituents Frequency Percentage Very often 2 Often 28 Occasional 52 Seldom 8 Never 10 Total 100 Pollution complaints show a peak in the dry season months of March, April, and May (Figure 8-2). This is the time when the water level is lowest. Pollution complaints are lowest in June and July, when heavy rains have arrived. 170 Figure 8-2. Frequency of complaints received by Barangay Captains relative to rainfall patterns in Mufioz, Nueva Ecija When asked what they would do if they had information on the pollution of the stream and they can identify the major polluters, the respondents gave the reactions presented in Table 8-18. Table 8-18. Reaction of respondents to pollution problems (N=121) Responding Reaction 27 % Talk to people, warning or admonishing them, or making them aware of the bad effects of pollution, and campaigning always against pollution 24 % Enact ordinances with or without penalty such as prohibiting the throwing of garbage and no fishing. Existing laws and regulations will have to be enforced and guards will have to be stationed to watch the stream, all these needing a meeting for training of needed personnel. 23 % Seek help from, and file complaints to, higher authorities 19 % Bolder steps have to be taken to improve the condition such as closing down the source of pollution (e.g. fermentation plant) or confiscating illegally-cut logs. Polluters can be called and given correct information. The leader should call for a clean-up and may even coordinate with the DSWD's food for work program. Ask people to boil all water and not to eat fish from the stream. 7 % There is no pollution here anyway and if there is, nothing can be done to stop the problem. It is very difficult to pinpoint the source of pollution since the (Pampanga) 171 The results reveal that more than a quarter of the respondents still make use of persuasion to obtain the necessary cooperation from the polluters. There is much hope however that the future would be better, as two-thirds of the respondents are taking bolder actions- from filing a complaint and calling for an assembly to resolve the problem, to enacting ordinances with penalties and closing pollution sources such as assembly plants. Only a very few (7%) of the respondents have indicated their feeling of helplessness in looking for solutions to pollution problems. Since community resources are very limited, one way to raise the funds to finance clean-ups or other environmental projects is to ask for contributions from the constituents in the form of additional tax. Asked whether their constituents will be willing to contribute, there is almost an equal percentage of respondents (53 % and 47 %) who think that their constituents would/would not pay additional taxes or contributions to clean up pollution. Eighteen (18) respondents who answered in the negative have the opinion that this tax is just an additional expense which will make life more difficult for ordinary people. Twelve (12) respondents answered in the negative because they thought that the stream is not polluted anyway, as the community does not throw garbage into it. Some respondents even added that since a dirty stream would be useless and the people are used to the dirty stream anyway, there was no incentive for a clean up. Eight (8) respondents answered that taxation is not the solution to the problem, that it is the government's problem, thus, they suggested that the government should prevent pollution. The above-mentioned reasons for answering in the negative show that the economic plight or poverty of the people may prevent them from contributing to whatever funding is necessary to clean-up the streams. When it was suggested to these people that these reasons were not adequate, they would resort to statements such as that the water is not polluted anyway or since it is already 172 too polluted. Lastly, respondents believed that it is the government's fault so the government should provide the solution. Reasons of those who answered in the affirmative include the idea that the tax is needed to raise the funds necessary for clean up which means the environment would be cleaner and more beautiful, diseases would be prevented and would improve everybody's future welfare, including that of the children. Additionally, some respondents thought that the tax would also mean economic welfare as a clean up would mean more fish stocks for fishermen and employment. 8.3.2 The Local Government Code (LGO and the Barangay Captains As mentioned earlier, Presidential Decree 1160 vests authority in officials to enforce pollution control and other environmental laws. It is therefore important to know whether these sentinels of the environment are even aware of these laws- the bases of their authority. When asked whether or not they have been informed of the LGC, 84% of those who answered the questions said they were informed while the 16% were either not informed of the L G C or have no opinion on the matter. The high proportion of informed respondents is encouraging, most of whom were informed through the other Local Government Units (LGU) as presented in Table 8-19. The same table indicates that the LGUs are more effective channels for informing the barangay captains of the code than either the national government agencies or the mass media. The high proportion of informed respondents however does not mean more action against pollution. When the respondents were asked whether or not they had been able to censure polluters employing the LGC, only 23 % answered in the affirmative. These censures were usually done in consultation with their council members and constituents, and arose from complaints by the health 173 officer or any constituent, witnessing actual pollution, or through discussions with other barangay captains. Table 8-19. Respondents' information channels for the Local Government Code (N=146) Percentajge Channel 41 through the Municipal Mayor's office 24 through the A B C president 13 through the governors office 8 through the DENR/PENRO/CENRO 7 through other means including the radio, the DILG, newspapers, their constituents, DOH 7 cannot recall how they came to know of the code Perceived effect of LGC on enforcement Although the respondents were already aware that overseeing the environment is one of their duties, a majority (88%) claimed that the LGC had given them additional power to enforce environmental standards in their barangays. Among the reasons cited to justify this include the following: The majority (52 %) contended that the LGC has become the legal basis of the barangay captain's powers, making them stronger since they had found it difficult to convince their constituents to follow rules just by their authority. Some (38 %) believed that the L G C would help them protect the environment and natural resources for the next generation by solving the problem of pollution in all places in the shortest possible time; and others (10 %) stated that the barangay captains have a better knowledge of pollution than other persons in the community since it is in the office of the barangay captain that pollution complaints are filed. Arguments for those who did not support the L G C include: Most (72 %) argued that the L G C was not clear enough and there is much to study in terms of the provisions, although they acknowledge that it is a law that has to be followed. Others (14 %) were not at all concerned with 174 the code, since they perceive their community to be relatively free of pollution or that pollution is not yet an issue. And an equal number (14 %) also answered in the negative because they believe that the role for pollution standard enforcement belongs to the national government, specifically the DENR, as they perceive the agency to have enough knowledge on pollution, aside from the reason that the office of the barangay captain does not have enough resources to use for enforcement. The role of the barangay in pollution control Since it is not only the office of the barangay captain that has jurisdiction on pollution control, it was necessary to know whether or not the respondents themselves want to take on the function. A majority (85 %) of the respondents agreed that the office of the barangay captain is the best office/agency of the government to enforce pollution standards and catch polluters. The following reasons were offered: Traditionally, people in the community air their complaints first to the barangay captain- they are the front liners and people confide in them more often. Since they may also be the easiest to approach and they know the people in the community better than others, their office is the best for enforcing pollution control in their communities. Additionally, the barangay captain is most familiar with the real situation at most times since his office is nearest in the area of pollution and he is one of the most informed persons in the community. His office is also the best to handle the problem since he answers to the community. Furthermore, it is the barangay captain's responsibility to apprehend law breakers within his jurisdiction. Those who disagreed furnished the following reasons: There is not enough strength and determination in barangay captains to fight pollution and enforce laws since a lot of people are hard-headed and undisciplined and the barangay captain cannot stay on guard at all times. Furthermore, it was argued that the barangay captain lacks the knowledge and the financial resources to enforce the law. Other comments include the belief that decision is always made at the 175 top and the office of the barangay captain as the weakest level of government would have to accept environmental decisions made at the top. One good suggestion was that the L G C should be studied first as there might be a lot of adverse consequences. It was pointed out, for example, that it might generate favouritism in the barangay- some would be permitted to pollute while others may be punished. 8.4 A cautious optimism for pollution control through the Barangay Captain There are indications presented in this chapter that the barangay captains who responded to the survey were familiar enough with their environment and were found to be qualified in assessing the condition of their local environment. Some of these perceptions however lagged behind what has been happening lately in the basin, specifically with regard to land-use, and there is some concern that their perceptions may not change if the government does not make available to them correct information regarding the condition of, and changes in, the environment. This chapter has also revealed that much has to be done to improve the barangay captain's capabilities, through their education on their responsibilities and power, as well as in providing them with the necessary resources, to carry out their functions in protecting the environment. A cautious optimism therefore is predicted in involving the barangay captains in the control of pollution, and for them to play their role in the overall environmental management and development of their communities. Chapter 9. S U M M A R Y , CONCLUSIONS, AND RECOMMENDATIONS The Pampanga River Basin is the major rice producing basin in the Philippines and it is therefore important to conserve its agricultural potential in order to sustain food production in the country. It was hypothesized that land-use changes have resulted in a deteriorating water quality, and that this is emerging as a major threat to the sustainability of agriculture in the basin. Although technological advancement has improved production, there are indications that the capacity of the basin for agricultural production has actually decreased due to undesirable changes in land-use. The goal of the research undertaking was to develop a framework by which interactions between land-use changes, water quality and institutional factors may be assessed in terms of historic development and projected scenarios by employing GIS techniques. The database used in the study came from various sources and was obtained using diverse methods. Field methods included monitoring 57 stations distributed on the streams throughout the basin which were sampled for nutrients (nitrate and phosphate) and other physical parameters (temperature, DO, TDS, COD and pH) weekly for a nine-month period. Land-use changes were determined by comparing maps through GIS overlay techniques, while land-use planning was investigated through participation in workshops and a review of past government plans. Data for institutional analysis were gathered through interviews, questionnaires and government reports. Throughout the study, GIS was employed both as an analysis tool and an integrating tool, and the aims were to link water quality deterioration with land-use. 9.1 Land-use dynamics and land-use planning The arable agricultural land in the basin increased from 45.1 % in 1953 to its all-time high value of 60.2 % in 1980. Since that time however, it declined to a low 53.4 % in 1993. The increases are attributed to conversion of grasslands, wetlands and forests for rice cultivation, while 177 the decrease is attributed to the encroachment of settlement areas which occurred due to rapid increases in population. This influenced the development of road networks which was needed to develop irrigated rice fields. The increase in rate of conversion to agricultural from other land-uses was 0.6% per year between 1953 and 1980, the agricultural land is now declining at 0.5 % annually. This is not considered compatible with sustainable agriculture. An analysis of the development plans of NED A revealed that land-use planning has never been given enough attention as a distinct planning process, resulting in these undesirable land-use changes. Among the planning problems that have sustained these land-use changes were; unclear terms of goals in plans, lack of data and information, lack of a dissenting voice, lack of appropriate legislation, and lack of co-ordination among and within the different levels of government. The evolution of the Nueva Ecija Land-use Plan was used as a case study illustrating the process of land-use planning to determine insights and overviews of provincial land-use planning. The process was beset with problems such as boundary disputes within and among the provinces and municipalities, the simplistic approach focused on a fixed percentage for land conversion, and the MPDCs' lack of authority to commit to the plan. These problems have emasculated the plan, making it just an exercise rather than an enforceable plan. The final draft of the plan will bring land-use changes ranging from a total conversion of agricultural lands to settlements for those municipalities rich in agricultural lands, and to re-classifying barelands and riverwash for municipalities already experiencing shortages of agricultural lands. Although the plan was envisioned to protect agricultural lands from conversion, the analysis suggests that it would accelerate conversion. 178 9.2 Water quality There is strong evidence that considerable changes in water quality in the Pampanga river and its tributaries, in both the spatial and temporal dimensions, have occurred. Generally, streams in or near the headwaters had more pristine quality than streams near the mouth of the river. The eruption of Mt. Pinatubo has unquestionably been responsible for increased levels of ortho-phosphate, TDS, COD, and increases in temperature in streams affected by the lahar flows. The pH had been within the normal range although there was a trend for decreasing values from 1962 to the present. In terms of DO, differences were found among stations during the rainy season, most probably explained by the washing of wastes that accumulated during the dry season, although there were no historic values since 1962 that were below the standard of 5 mg/1. Higher nitrate-N concentrations were registered downstream of stations with highly populated settlement areas, but different streams responded differently in the different seasons. Precipitation which is influenced by the geography of the stations, played a role in some of these response variations. Nitrate-nitrogen concentration in the streams has increased since 1964. Overall, in terms of pollution, values observed in the study were within the acceptable values for Class C waters, but were higher when compared with other river systems in the Philippines, suggesting that contamination problems exist. 9.3 Interaction between land-use and water quality Streams with catchments having the same predominant land-use classification exhibited similar trends in water quality, and the relationship between a buffered area and water quality was always better than the relationship between total basin areas and water quality, indicating that water quality is much more influenced by land-uses adjacent to the streams rather than by the total area of the streams' catchment. Although no single buffer classification gave a consistent 179 relationship, the 500 meter buffer on all streams gave best values. The differences observed in water quality parameters among streams in different seasons may be due partly to the differences in the dominance of surface or groundwater contribution to the stream. The effect of runoff however is altered by the type of land-use, specifically the presence of rice fields which intercepted and retained runoff during the start of the planting season. This resulted in the negative relationships of the area devoted to rice production and the water quality parameters. The very high values of TDS and COD are once again related to the lahar as land-use cover. In terms of animal farms, the general inference is that different animal species in different area classifications affect the water quality of the streams at different flow periods. Hog farms and poultry farms closer to streams during the low flow periods, and ruminants within the total catchment area during the rising limb of the high flow period, have significant adverse relationships. Of the two nutrients studied, the variation of nitrate-N concentration is closely related to animal production and human population, while ortho-phosphate variation is explained almost totally by variation in land-use cover (non-point sources). 9-4 A framework for nitrogen management The management of nitrate-N in streams was illustrated by using a nitrogen budget that integrates land-use and water quality interactions. The major contributors to fluxes of nitrogen in the basin were identified and catchments with surpluses (termed as hotspots) of nitrogen concentration were located. The nitrogen budgets revealed that animal manure contributes more than half, and inorganic fertilizer almost a quarter, to the total nitrogen in the basin, while crop uptake which should be the major sink of nitrogen accounts for a little more than 40 percent of the total sink. The hotspots, or catchments with the highest expected nitrogen values include those with large settlement areas, or with a very high animal population, or a combination of both. Two 180 scenarios were studied; one dealing with the increasing animal production, and the other dealing with the loss of agricultural lands. To compare the results from the management scenarios, the nitrate-nitrogen concentration were predicted based on the relationship between the expected total nitrogen value and the observed nitrate-nitrogen concentration at each station. It was revealed that even with a three-fold increase in animal production, only one station would exceed the limit of 10 ppm nitrate-nitrogen. Furthermore, the predicted nitrate values increase as more agricultural land is lost (up to 5% loss of agricultural land), but at higher losses, decreases in predicted nitrate concentrations occur. 9.5 Future for Land-use and Water Quality : Perceptions of Barangay Captains The survey which included 172 barangay captains revealed environmental perceptions, opportunities and problems faced by the barangay when dealing with the management of land-use and water resources in the basin. Results indicated that the typical barangay captain is a farmer, more than 40 years old, has been in the community for 30 years or more, and is very much concerned with the state of the environment in the community. These local leaders believed that the most pressing problem in their communities is economic in origin, but in terms of environmental problems, deforestation was perceived to be the most pressing. However, their perceptions on land-use did not agree with the data on land-use changes in the basin reported in this study. The streams evaluated were perceived as just a little polluted but those perceived to be polluted were streams along the lower reaches of the river. The survey further revealed that pollution is perceived to be of recent occurrences and that although the area is mainly agricultural, the respondents insisted that the manufacturing industry in the region is a likely cause of the problem. The search for evidences of enforcement reveals that the most common form of enforcement is through persuasion. The high proportion of respondents were informed of the LGC 181 which is encouraging. They believe that they can enforce pollution standards and catch polluters, but so far only a few have been able to censure polluters employing the L G C . A cautious optimism therefore is anticipated in involving the barangay captains in the control of pollution. They are capable to play an important role in the overall environmental management and development of their communities. 9.6 Recommendations 9.6.1 Improve Land-use Planning Too much land conversion is occurring in the study area and this is certainly not compatible with sustainable agriculture, especially if this conversion is primarily from high quality agricultural lands to urban land-use. Therefore it is only sensible to constrain development to minimize land conversion. There was an opportunity in the Nueva Ecija Land-use Plan to achieve this goal, but even with its good intentions, the plan failed to ensure that the rate of converting agricultural lands was minimized. This is not supporting the sustainable agriculture concept. While much of the plan should be upheld, the planning principles and processes used had significant gaps and hence should be improved. It is extremely important that a wider range of options for the process should be sought. Land-use information need to be accurate and comprehensive, and options must be addressed in a realistic manner at the provincial level. 9.6.2 Develop a New Monitoring Network The recent problems relating to the closure of plants to reduce the input from point sources such as the distilleries and piggeries are due to the fact that data gathered by the E Q D cannot be used to provide proof of pollution - a problem that is traceable to the lack of a proper monitoring network. Therefore, a new and improved monitoring network should be developed in order to 182 examine the trends in water quality in the basin as well as to determine the effects of land-use on water quality. This monitoring network must include monitoring of pollution sources, especially in regions considered as hotspots. The DENR never made use of their data in defending their position against criticism because there is a major difficulty with the interpretability of the data in reflecting trends or relationships. Although the network of stations used in the study was developed for research, it may serve the purposes of the DENR as well, especially with some modifications in terms of allocation of stations which may now be based on the relationship of land-use and water quality resulting from this study. However, the establishment of a monitoring network should be co-ordinated with other agencies which monitor the same streams for water quality in an effort to reduce redundant data and improve coverage of streams and/or more frequency of sampling with the same amount of funds used, and with other agencies that monitor for inputs such as the Bureau of Animal Industry and the Bureau of Agricultural Extension. 9.6.3 Enforce Animal Waste Management Operation Animal production is a major thrust of the government and is expected to increase substantially in the basin in the immediate future. Since it is the major reason for increased nitrate-nitrogen concentrations in streams, the best practice for controlling nitrate accumulation in the streams is the management of nitrogen and water outputs from the farms. Although large commercial operations have waste treatment facilities, these are not always operational. Strict enforcement should therefore be considered, aside from the provision of technical advice on waste management from the government. The goals of increasing productivity through intensive rice production and increasing animal production may be combined in order to limit pollution of the streams in the basin through proper nitrogen management. This will be economically beneficial to farmers since inorganic 183 fertilizers are very expensive. This, however, needs the cooperation of the rice producers. The problem of correct timing in using animal manure as fertilizer may be solved with cooperation between the animal raisers and rice farmers. 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Pollution of soils and watercourses by wastes from livestock production systems. In Pollution in livestock and production systems. Dewi, LA. (ed). United Kingdom: CAB International, pp 189- 204. Wong, J.L.G. 1993. Evaluating the water resource impacts of afforestation in upland Britain. Proceedings of GIS '93 Symposium. Vancouver, British Columbia, Canada, February 1993. pp. 319-324. 193 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 2 93 11 11 1330 29.0 8.20 93 8.3 0.50 0.10 43 21 93 11 13 1200 30.1 7.77 109 9.7 1.60 0.56 7 27 93 11 13 1600 30.6 7.89 134 6.8 0.70 0.26 8 19 93 11 16 905 25.3 8.07 142 10.3 19 93 11 16 910 25.2 8.13 141 10.1 19 93 11 16 1015 26.1 8.04 137 9.7 19 93 11 16 1100 27.2 7.84 141 9.7 19 93 11 16 1527 28.9 8.31 138 9.0 19 93 11 16 1609 26.3 8.22 123 9.5 19 93 11 16 1615 28.2 8.33 139 9.3 10 93 11 17 900 27.9 8.04 117 6.2 1.60 0.22 9 8 93 11 17 1035 25.8 8.04 134 7.6 1.25 3.30 5 19 93 11 17 1100 30.5 8.48 143 5.2 0.70 0.31 7 7 93 11 17 1435 28.2 8.12 137 6.7 1.30 0.40 27 45 93 11 20 930 28.0 8.00 153 6.4 1.70 2.35 21 47 93 11 20 1120 28.8 7.82 210 6.3 0.29 36 44 93 11 20 1430 29.6 7.91 166 6.3 2.75 50 37 93 11 22 940 26.2 8.24 152 7.6 1.90 20 11 93 11 22 1245 26.3 8,26 109 6.9 8.00 35 54 93 11 23 1040 27.3 7.72 148 6.1 0.87 21 55 93 11 23 1120 27.3 7.94 105 7.3 3.25 37 56 93 11 23 1230 27.7 7.85 111 7.5 3.75 19 28 93 11 23 1520 28.0 7.25 99 7.8 1.00 2.95 24 4 93 12 4 1230 22.4 8.21 31 6.9 0.00 0.33 12 7 93 12 4 1500 27.7 8.00 93 5.3 2.40 0.21 87 8 93 12 4 1600 26.8 7.91 92 6.7 0.00 0.01 68 10 93 12 4 1700 28.8 8.25 114 6.7 0.50 0.19 7 21 93 12 5 945 23.9 8.25 98 5.7 0.50 1.10 3 52 93 12 5 1000 27.0 7.59 106 6.9 0.70 0.13 9 27 93 12 5 1015 24.3 7.63 104 6.4 2.20 0.22 13 51 93 12 5 1100 28.1 7.19 66 5.2 0.00 0.93 25 50 93 12 5 1115 27.9 7.38 124 6.8 0.50 0.18 46 49 93 12 5 1130 27.9 7.65 135 6.9 0.60 0.96 15 48 93 12 5 1200 27.3 7.73 95 7.0 0.00 0.18 10 45 93 12 5 1300 28.3 7.94 87 6.2 0.50 0.13 1 18 93 12 5 1330 24.8 7.66 106 9.1 1.00 0.12 15 17 93 12 5 1340 25.4 7.88 159 7.8 2.80 0.52 9 16 93 12 5 1350 24.6 7.58 106 7.0 0.30 0.06 25 11 93 12 5 1420 23.9 7.77 99 7.7 0.40 0.66 102 28 93 12 10 1000 26.3 7.85 107 6.8 0.40 0.17 15 44 93 12 10 1130 26.3 8.02 105 6.5 0.30 0.27 35 55 93 12 10 1230 26.7 7.46 120 6.7 1.10 0.29 33 54 93 12 10 1300 26.8 7.88 128 6.7 0.10 0.36 23 56 93 12 10 1500 27.1 7.92 111 6.2 0.10 0.18 23 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries (cont.p 2) 194 Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (DegC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 52 93 12 11 1000 27.3 8.05 115 6.9 0.60 0.77 8 51 93 12 11 1200 26.7 7.39 94 6.7 0.80 0.09 41 50 93 12 11 1210 26.9 7.53 133 6.5 0.00 0.10 42 49 93 12 11 1220 26.6 8.36 166 6.2 1.90 0.13 15 48 93 12 11 1300 27.0 8.04 120 7.0 0.20 0.16 7 45 93 12 11 1330 27.1 8.10 93 6.7 0.40 0.08 9 47 93 12 11 1430 26.7 8.00 135 6.7 0.40 0.15 19 27 93 12 11 1530 26.6 8.15 103 5.8 1.30 0.13 17 18 93 12 11 1600 26.6 8.12 105 6.0 0.90 0.06 26 4 93 12 12 1230 23.7 8.00 48.5 7.4 0.60 0.10 2 7 93 12 12 1448 26.3 8.16 97 6.7 0.40 0.08 27 8 93 12 12 1515 26.3 8.16 97 6.7 0.10 0.11 31 10 93 12 12 1555 28.0 8.40 121 6.2 1.80 0.19 4 21 93 12 13 1000 25.8 8.30 91 6.8 0.20 0.13 11 28 93 12 13 1345 27.7 8.01 111 6.2 0.00 0.11 23 27 93 12 13 1415 28.9 8.14 99 6.0 0.20 0.21 11 18 93 12 13 1430 28.0 7.81 112 6.2 0.20 0.08 27 17 93 12 13 1440 28.2 7.84 149 6.2 1.00 0.25 16 16 93 12 13 1455 27.7 7.94 103 6.2 0.30 0.08 23 52 93 12 16 1005 26.4 8.03 120 6.7 0.40 0.09 6 51 93 12 16 1030 26.5 7.78 104 6.6 1.10 0.06 38 50 93 12 16 1045 25.9 7.64 123 6.8 0.00 0.47 49 49 93 12 16 1050 27.0 8.46 182 6.4 0.60 0.12 14 48 93 12 16 1200 25.5 8.08 76 6.9 0.70 0.44 23 45 93 12 16 1230 25.8 7.91 55 6.7 0.90 0.14 18 46 93 12 16 1310 26.7 7.91 233 6.5 0.70 2.55 59 47 93 12 16 1315 26.6 8.13 156 6.7 0.20 0.33 13 47 93 12 16 1410 27.2 7.84 108 6.4 0.70 0.07 45 57 93 12 17 1220 26.1 8.04 98 6.7 0.10 0.26 36 56 93 12 17 1330 26.9 7.97 82 6.4 2.50 0.25 53 55 93 12 17 1350 25.7 7.95 77 6.9 0.00 0.26 56 54 93 12 17 1400 26.2 7.91 110 6.7 0.25 0.37 23 44 93 12 17 1430 24.9 8.10 83 7.3 0.20 0.27 49 28 93 12 17 1540 24.6 7.93 87 7.1 2.70 0.09 63 2 93 12 18 800 25.0 7.35 4.7 0.36 4 93 12 18 1200 23.5 7.81 37 7.5 0.50 0.07 11 7 93 12 18 1500 25.8 8.25 103 6.9 1.90 0.18 32 8 93 12 18 1540 26.1 8.03 88 6.7 1.10 0.13 38 10 93 12 18 1635 27.4 8.35 114 6.3 1.80 0.19 15 33 93 12 19 1000 26.9 8.44 137 6.5 0.40 0.23 27 31 93 12 19 1310 30.2 8.55 175 5.6 0.50 0.16 10 30 93 12 19 1425 29.0 7.78 271 5.9 1.80 0.43 18 32 93 12 19 1450 29.7 8.24 172 5.7 2.40 0.15 13 36 93 12 19 1515 27.0 7.31 93 6.4 0.30 0.22 30 195 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 3) Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 37 93 12 19 1530 29.1 8.29 157 5.9 0.50 0.26 21 11 93 12 19 1545 27.5 7.84 97 6.3 0.90 0.14 21 19 93 12 21 950 27.4 8.40 105 6.4 1.10 0.29 16 21 93 12 21 1010 29.4 7.58 95 5.9 0.50 0.27 13 28 93 12 21 1440 28.3 7.65 107 5.7 0.60 0.19 34 27 93 12 21 1520 28.9 7.63 108 6.0 1.10 0.25 10 18 93 12 21 1535 27.9 7.50 106 6.2 1.60 0.14 26 17 93 12 21 1550 28.0 7.27 137 6.2 0.50 0.18 24 16 93 12 21 1600 27.9 7.34 107 6.2 0.90 0.14 32 14 93 12 21 1620 27.9 7.16 111 6.2 0.80 0.19 41 13 93 12 21 1650 27.9 7.13 154 6.2 0.70 1.73 43 16 93 12 22 925 26.6 7.93 111 6.5 1.40 0.21 25 39 93 12 22 1000 26.9 8.01 155 6.5 0.80 0.22 26 43 93 12 22 1150 29.6 8.22 940 5.7 0.60 0.82 360 56 93 12 22 1345 29.1 7.84 120 6.0 1.20 0.25 23 55 93 12 22 1420 28.1 7.83 121 6.2 1.30 0.22 55 54 93 12 22 1435 28.5 7.86 157 6.1 1.00 0.41 38 44 93 12 22 1520 27.9 7.97 121 6.2 0.40 0.21 23 52 93 12 23 900 26.7 7.65 126 6.5 0.70 0.05 0 51 93 12 23 945 25.8 7.02 115 6.8 0.20 0.04 38 50 93 12 23 1000 25.3 7.45 126 6.9 0.10 0.15 28 49 93 12 23 1100 27.1 7.55 176 6.4 0.60 0.09 15 48 93 12 23 1135 27.0 7.61 117 6.4 0.40 0.16 0 45 93 12 23 1315 27.0 7.39 169 6.4 0.80 0.11 0 46 93 12 23 1400 26.0 7.60 213 6.7 2.25 1.71 27 42 93 12 24 1200 27.9 7.30 340 6.2 0.40 0.59 26 43 93 12 24 1350 28.7 7.37 890 6.0 0.30 0.65 345 40 93 12 24 1500 28.1 7.35 307 6.1 1.50 0.73 67 39 93 12 24 1555 25.7 7.40 159 6.9 1.20 0.22 32 16 93 12 24 1625 25.6 7,38 134 6.9 0.30 0.07 24 14 93 12 24 1655 24.8 7.24 113 7.1 1.10 0.07 33 13 93 12 24 1715 24.6 7.34 132 7.1 0.20 0.57 32 33 93 12 25 930 23.1 7.74 150 7.6 0.40 0.22 27 31 93 12 25 1100 25.0 8.02 183 7.0 1.90 0.11 1 30 93 12 25 1200 26.1 7.53 296 6.7 2.30 0.51 6 32 93 12 25 1325 27.1 8,13 166 6.4 0.40 0.13 8 36 93 12 25 1410 25.1 6.89 97 7.0 5.00 0.09 36 37 93 12 25 1450 27.1 7.97 136 6.4 3.30 0.18 21 11 93 12 25 1540 28.8 7.56 119 8.1 2.80 0.15 22 4 93 12 27 1000 20.8 7.65 50 8.5 1.30 0.04 20 7 93 12 27 1336 22.4 7.91 124 7.8 0.60 0.09 31 8 93 12 27 1410 22.6 7.78 115 7.8 0.80 0.07 30 10 93 12 27 1530 22.6 7.90 124 7.8 0.90 0.05 13 57 93 12 29 1100 25.0 7.62 134 7.0 1.30 0.24 27 56 93 12 29 1210 25.2 7.92 140 6.9 0.30 0.26 37 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 4) 196 Station year month day time Temp pH TDS DO nitrate o-P04 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 55 93 12 29 1340 25.6 7.48 123 6.9 0.90 0.23 34 54 93 12 29 1350 25.6 7.51 150 6.9 0.90 0.41 37 44 93 12 29 1435 26.6 7.60 99 6.7 2.20 0.34 39 28 93 12 29 1600 26.1 7.58 115 6.7 3.00 0.20 23 27 93 12 29 1630 25.5 7.76 78 6.9 0.10 0.37 45 21 93 12 30 1040 26.3 7.81 86 8.7 0.40 0.24 20 18 93 12 30 1330 27.1 7.63 105 8.1 0.80 0.06 26 17 93 12 30 1400 27.8 7.57 153 8.0 0.80 0.13 65 16 93 12 30 1440 28.1 7.54 103 7.8 0.70 0.15 68 14 93 12 30 1505 27.4 7.31 115 8.1 0.20 0.07 75 13 93 12 30 1530 28.1 7.43 129 7.8 0.40 0.61 73 33 93 12 31 1020 26.8 8.17 141 8.7 0.50 0.16 35 31 93 12 31 1200 29.2 8.57 176 6.8 0.40 0.07 22 30 93 12 31 1400 29.7 7.60 292 7.3 1.30 0.46 29 32 93 12 31 1430 32.1 8.61 162 6.4 0.70 0.09 39 36 93 12 31 1500 28.5 7.23 86 7.7 0.60 0.01 73 37 93 12 31 1515 30.6 8.17 132 7.0 0.10 0.04 38 11 93 12 31 1600 28.8 7.75 110 7.6 0.90 0.50 46 10 94 1 2 900 27.6 7.81 128 7.0 0.50 0.25 10 8 94 1 2 945 26.5 7.95 111 7.4 0.30 0.36 18 7 94 1 2 1015 27.1 7.83 128 8.1 0.30 0.05 12 4 94 1 2 1330 25.1 7.64 35 7.8 0.40 0.02 9 46 94 1 3 1000 26.7 7.64 189 7.6 0.40 2.31 28 48 94 1 3 1030 28.4 7.96 145 7.1 0.70 0.09 2 49 94 1 3 1050 26.8 7.73 151 7.0 0.60 0.12 10 50 94 1 3 1055 26.8 7.45 163 7.6 1.30 0.05 57 51 94 1 3 1105 26.5 7.41 140 7.7 0.10 0.04 51 52 94 1 3 1130 27.9 7.66 133 7.2 0.50 0.03 13 45 94 1 3 1230 28.8 8.21 119 6.9 1.00 0.04 11 16 94 1 4 830 27.0 7.64 125 6.7 0.10 0.01 28 39 94 1 4 1000 28.0 7.81 148 6.3 0.40 0.17 69 42 94 1 4 1430 31.4 8.53 340 6.8 0.30 0.07 43 40 94 1 4 1520 28.7 7.85 149 6.7 0.40 0.04 68 57 94 1 10 1115 28.9 7.75 112 7.3 0.20 0.17 32 56 94 1 10 1220 30.0 7.63 111 7.1 0.10 0.19 54 55 94 1 10 1300 28.9 7.89 109 7.2 0.10 0.13 57 54 94 1 10 1320 29.7 7.66 146 7.0 0.30 0.22 64 53 94 1 10 1410 30.3 7.67 134 6.8 0.10 0.17 62 44 94 1 10 1500 30.1 7.82 114 6.9 0.70 0.09 57 28 94 1 10 1600 29.4 8.00 112 7.1 0.10 0.11 52 27 94 1 10 1630 29.8 8.22 105 7.0 0.40 0.07 39 18 94 1 10 1705 29.1 7.73 113 7.1 0.50 0.15 50 33 94 1 11 1100 25.2 8.15 150 7.4 0.60 0.09 43 31 94 1 11 1200 30.1 8.25 181 6.9 0.90 0.05 9 32 94 1 11 1301 32.4 8.07 157 6.5 0.20 0.08 33 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 5) 197 Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DcgC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/I) 30 94 1 11 1330 30.2 7.78 301 7.1 1.60 0.27 15 38 94 1 11 1430 32.2 8.06 164 6.5 0.60 0.10 35 36 94 1 11 1700 28.5 7.31 103 7.4 37 94 1 11 1715 29.2 7.68 121 7.4 0.10 0.01 46 11 94 1 11 1750 28.0 7.50 89 7.8 0.10 0.01 48 4 94 1 12 1230 23.3 7.82 35.9 7.6 0.60 0.01 0 8 94 1 12 1530 26.1 7.68 115 6.7 0.30 0.04 7 7 94 1 12 1551 26.7 8.24 123 6.5 0.90 0.03 0 10 94 1 12 1740 27.3 8.18 129 6.4 0.30 0.07 1 21 94 1 13 1000 26.6 7.89 101 7.8 0.70 0.29 16 46 94 1 13 1215 27.6 7.79 209 7.3 3.40 3.63 30 48 94 1 13 1230 29.1 7.71 158 6.9 0.50 0.33 12 49 94 1 13 1235 27.8 7.85 199 7,2 0.40 0.12 8 50 94 1 13 1240 28.3 7.62 176 7.1 0.20 0.08 32 51 94 1 13 1255 27.4 7.35 137 7.3 52 94 1 13 1330 28.5 7.45 138 7.1 1.30 0.10 1 45 94 1 13 1500 30.7 8.33 138 6.4 0.70 0.09 8 2 94 1 14 800 26.3 7.86 5.8 0.35 57 94 1 15 1120 28.3 7.51 143 7.8 0.30 0.17 29 56 94 1 15 1200 28.1 7.61 150 7.8 0.40 0.19 16 53 94 1 15 1315 29.0 7.20 173 8.0 0.40 0.15 49 54 94 1 15 1400 29.8 7.28 187 7.6 0.50 0.13 35 55 94 1 15 1445 28.1 7.48 154 8.2 0.50 0.18 22 44 94 1 15 1515 28.1 7.53 151 8.2 0.40 0.12 22 28 94 1 15 1630 27.9 7.73 140 7.9 0.90 0.09 19 13 94 1 17 900 25.9 7.61 152 6.7 14 94 1 17 915 25.9 7.67 131 6.7 16 94 1 17 930 26.1 7.58 133 6.7 0.50 0.20 47 39 94 1 17 1015 26.3 7.83 146 6.7 0.10 0.23 61 40 94 1 17 1130 27.9 7.70 147 6.2 0.70 0.22 34 41 94 1 17 1135 26.5 8.24 740 6.6 0.10 0.14 126 43 94 1 17 1200 30.2 8.57 890 5.6 0.20 0.55 459 42 94 1 17 1330 30.3 8.47 300 6.7 0.40 0.62 17 30 94 1 17 1545 28.7 7.77 310 7.3 0.50 0.46 34 32 94 1 17 1620 29.4 7.74 164 7.3 0.10 0.11 24 37 94 1 17 1700 27.4 8.21 137 7.7 0.40 0.13 41 11 94 1 17 1730 26.0 7.85 118 8.0 0.50 0.10 44 10 94 1 19 930 26.4 7.66 135 7.0 0.40 0.12 6 8 94 1 19 1020 24.5 7.52 154 7.8 0.60 0.04 8 7 94 1 19 1120 24.7 8.05 136 7.6 0.70 0.04 2 33 94 1 19 1400 27.9 8.09 153 7.2 0.50 0.06 5 31 94 1 19 1500 29.1 8.11 173 7.3 0.40 0.07 4 36 94 1 19 1545 26.3 7.31 111 7.8 37 94 1 19 1550 27.9 8.19 139 7.1 0.50 0.03 21 11 94 1 19 1714 27.1 7.83 128 7.6 0.40 0.06 21 198 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries (cont.p 6) Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DegC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/I) 16 94 1 20 940 26.3 7.27 137 8.3 0.30 0.19 34 17 94 1 20 1010 25.5 7.33 148 8.4 0.20 0.07 32 18 94 1 20 1025 26.3 7.65 135 8.3 0.80 0.06 26 27 94 1 20 1045 27.5 7.84 160 7.8 0.90 0.03 31 21 94 1 20 1110 25.8 7.90 102 7.8 0.80 0.09 11 46 94 1 20 1300 27.3 7.46 161 7.9 0.70 2.61 29 48 94 1 20 1315 28.2 7.99 163 7.6 2.40 0.24 6 49 94 1 20 1335 27.7 7.59 218 7.9 0.30 0.06 14 50 94 1 20 1350 25.7 7.62 210 8.5 0.40 0.07 41 52 94 1 20 1420 28.4 7.33 144 7.6 0.60 0.07 12 45 94 1 20 1640 29.7 7.93 146 7.1 0.70 0.07 8 2 94 1 28 800 26.0 6.82 5.5 57 94 2 3 1140 27.9 7.61 168 7.2 0.80 0.03 49 56 94 2 3 1230 28.9 7.55 150 6.9 1.10 0.09 19 53 94 2 3 1345 27.1 7.27 153 7.1 0.90 0.09 34 54 94 2 3 1410 27.0 7.40 166 7.2 1.10 0.09 39 55 94 2 3 1430 26.7 7.39 192 7.3 0.90 0.18 29 44 94 2 3 1501 27.2 7.62 153 6.6 0.70 0.18 29 27 94 2 3 1545 27.4 8.20 124 6.6 1.00 0.07 18 28 94 2 3 1615 26.9 7.62 136 6.7 1.40 0.14 40 18 94 2 3 1715 26.5 7.81 137 6.7 0.90 0.12 19 16 94 2 3 1800 26.1 7.58 131 6.9 0.90 0.17 25 4 94 2 4 1430 24.2 7.61 33.9 8.8 1.00 0.06 0 7 94 2 4 1605 28.2 7.67 133 7.4 0.80 0.05 4 8 94 2 4 1640 26.3 7.63 105 8.1 0.50 0.05 7 10 94 2 4 1717 27.3 7.88 125 7.7 0.30 0.09 9 33 94 2 5 1008 25.4 8.17 149 7.1 0.10 0.15 29 31 94 2 5 1100 28.3 8.01 188 7.1 0.50 0.17 18 30 94 2 5 1230 29.6 7.57 308 7.0 0.50 0.75 42 32 94 2 5 1301 30.4 8.90 154 6.7 0.90 0.10 83 36 94 2 5 1320 25.6 7.19 115 8.3 37 94 2 5 1340 28.2 8.15 133 7.4 1.50 0.12 17 11 94 2 5 1418 28.3 7.53 134 7.4 0.80 0.11 16 45 94 2 6 1030 31.1 7.49 205 6.3 1.20 0.08 5 40 94 2 6 1057 29.6 7.59 163 7.8 1.00 0.12 29 41 94 2 6 1059 28.0 8.19 830 7.8 0.40 0.03 157 43 94 2 6 1210 34.0 8.46 880 6.0 0.20 0.77 847 50 94 2 6 1215 30.2 7.14 252 8.0 1.00 0.10 45 52 94 2 6 1255 29.2 7.10 155 6.8 0.80 0.03 20 42 94 2 6 1310 34.1 8.00 355 6.3 0.70 0.61 29 51 94 2 6 1320 26.5 6.98 138 7.7 48 94 2 6 1400 28.7 7.60 178 7.3 0.90 0.50 15 46 94 2 6 1420 28.6 7.29 206 7.3 2.20 2.75 28 39 94 2 6 1445 30.0 7.29 154 7.9 0.90 0.11 33 16 94 2 6 1520 29.9 7.21 132 7.9 0.90 0.10 20 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries (cont.p 7) Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (Deg C) units (PPm) (mg/1) (mg/1) (mg/1) (mg/1) 21 94 2 6 1535 29.6 8.08 97 7.0 0.70 0.03 3 14 94 2 6 1545 28.6 7.11 130 8.4 0.90 0.07 71 13 94 2 6 1600 28.8 7.15 139 8.3 0.90 0.84 27 94 2 6 1625 31.0 7.90 144 6.6 1.00 0.15 21 18 94 2 6 1653 29.3 7.75 140 7.1 1.00 0.10 14 17 94 2 6 1715 28.0 7.53 146 6.9 0.90 0.07 32 16 94 2 6 1745 28.7 7.67 138 6.2 0.30 0.09 32 13 94 2 6 1805 28.7 7.27 139 6.4 2.00 0.60 26 57 94 2 10 1100 29.5 7.49. 169 7.4 1.50 0.12 69 56 94 2 10 1150 28.9 7.58 158 6.9 1.00 0.16 22 53 94 2 10 1235 28.4 7.32 167 6.7 2.00 0.17 37 54 94 2 10 1300 28.1 7.42 189 6.9 1.00 0.19 27 55 94 2 10 1315 28.7 7.86 160 6.7 0.80 0.18 24 44 94 2 10 1355 28.5 7.51 168 6.7 0.90 0.11 37 28 94 2 10 1525 28.7 7.68 141 6.7 1.50 0.15 49 27 94 2 10 1600 28.1 8.06 171 6.9 0.80 0.05 12 18 94 2 10 1625 28.3 7.62 137 6.8 2.00 0.14 37 17 94 2 10 1700 27.3 7.45 143 7.1 1.50 0.06 22 16 94 2 10 1718 27.6 7.44 132 7.0 1.80 0.16 34 2 94 2 11 800 28.0 7.26 6.0 33 94 2 11 1010 26.5 8.16 152 7.4 2.60 0.09 0 31 94 2 11 1100 28.8 7.98 182 6.7 1.90 0.05 0 32 94 2 11 1140 39.7 8.28 174 7.1 0.80 0.05 29 36 94 2 11 1208 26.8 7.11 117 8.4 0.80 0.13 27 37 94 2 11 1220 29.2 8.36 130 6.3 2.00 0.11 0 11 94 2 11 1320 29.6 7.39 118 7.4 2.00 0.08 5 7 94 2 11 1430 29.4 7.58 131 6.3 0.70 0.05 0 8 94 2 11 1500 28.1 7.41 97 6.6 1.40 0.07 0 16 94 2 12 1015 22.7 7.53 121 7.0 0.90 0.09 0 39 94 2 12 1105 29.2 7.28 151 6.6 1.00 0.14 39 40 94 2 12 1150 29.3 7.30 159 7.4 1.80 0.14 8 43 94 2 12 1245 35.7 8.29 850 4.8 0.10 0.83 1650 42 94 2 12 1343 34.9 7.93 290 6.6 0.40 0.68 35 39 94 2 12 1520 31.3 7.13 153 7.1 1.10 0.16 20 16 94 2 12 1610 30.0 7.24 154 7.2 0.70 0.12 14 14 94 2 12 1635 29.9 7.00 117 7.2 1.10 0.10 30 6 94 2 13 1200 26.0 7.59 104 7.6 0.80 0.09 0 45 94 2 15 955 27.1 7.24 171 6.8 0.90 0.11 10 50 94 2 15 1040 27.1 7.08 261 6.9 0.50 0.06 19 52 94 2 15 1115 29.0 6.92 148 6.4 0.40 0.09 2 48 94 2 15 1145 28.7 7.28 184 7.0 0.70 0.39 19 46 94 2 15 1200 28.4 7.35 366 7.1 2.30 3.00 48 21 94 2 15 1330 27.8 7.43 127 7.3 0.30 0.20 35 27 94 2 15 1410 29.6 7.52 258 6.7 14 18 94 2 15 1435 28.9 7.01 147 6.9 1.90 0.24 66 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries (cont.p 8) 200 Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DegC) units (ppm) (mg/1) (mg/1) (me/i) (mg/1) 17 94 2 15 1510 28.4 6.84 150 7.1 0.80 0.11 17 16 94 2 15 1530 29.4 7.01 117 6.8 1.00 0.16 28 57 94 2 16 1120 29.4 7.07 149 5.8 1.20 0.08 22 56 94 2 16 1210 29.4 6.91 143 7.2 2.50 0.23 24 54 94 2 16 1400 29.9 6.85 168 5.7 0.40 0.21 18 55 94 2 16 1410 29.1 7.07 136 7.4 1.80 0.22 47 44 94 2 16 1450 29.6 7.10 135 7.4 1.80 0.22 42 53 94 2 16 1530 30.1 6.81 149 7.1 0.90 0.23 57 28 94 2 16 1545 29.1 7.30 121 7.5 1.10 0.16 0 27 94 2 16 1620 30.4 7.73 124 7.1 0.70 0.14 0 18 94 2 16 1650 29.0 7.12 122 7.5 1.20 0.18 9 17 94 2 16 1720 28.2 6.89 148 7.8 0.80 0.17 13 16 94 2 16 1740 28.6 7.25 124 7.6 1.50 0.17 0 33 94 2 17 1005 25.7 7.77 162 6.8 1.00 0.23 12 31 94 2 17 1125 30.4 198 5.5 1.80 0.13 4 32 94 2 17 1215 31.3 169 5.3 2.00 0.12 17 36 94 2 17 1245 28.1 130 6.2 1.10 0.09 15 37 94 2 17 1300 31.0 128 5.4 2.00 0.09 22 11 94 2 17 1355 30.7 127 6.8 0.70 0.08 1 7 94 2 17 1512 29.4 130 7.4 1.40 0.06 9 8 94 2 17 1550 28.2 112 7.8 0.70 0.06 0 10 94 2 17 1625 30.6 127 7.0 0.70 0.17 0 42 94 2 18 1340 32.0 330 6.4 0.40 0.63 22 43 94 2 18 1430 32.9 840 6.0 1.00 0.85 622 40 94 2 18 1520 30.5 158 7.2 1.80 0.14 17 39 94 2 18 1610 30.7 150 7.2 1.10 0.13 30 16 94 2 18 1700 29.9 124 6.5 1.30 0.09 3 14 94 2 18 1725 29.3 115 7.0 1.00 0.16 21 13 94 2 18 1745 28.6 117 6.4 1.60 0.55 7 45 94 2 23 1030 28.4 175 6.4 2.10 0.11 0 50 94 2 23 1117 28.0 270 1.70 0.07 47 52 94 2 23 1145 29.1 153 0.90 0.12 8 48 94 2 23 1210 31.1 179 5.8 0.80 0.44 6 46 94 2 23 1230 30.5 202 4.8 1.70 1.87 7 21 94 2 23 1350 30.2 109 6.5 0.70 0.18 1 18 94 2 23 1435 30.7 132 6.0 1.60 0.20 10 17 94 2 23 1510 29.7 138 5.6 0.90 0.11 9 16 94 2 23 1535 30.4 128 6.1 1.10 0.21 50 2 94 3 3 800 26.0 8.20 5.8 6 94 3 6 1345 30.1 7.52 155 6.4 0.70 0.02 0 57 94 3 7 1200 30.7 168 0.9 0.20 46 56 94 3 7 1300 30.2 142 6.5 1.20 0.13 38 53 94 3 7 1425 30.9 299 6.0 0.10 0.28 112 54 94 3 7 1450 31.7 300 5.5 0.40 0.19 30 55 94 3 7 1505 30.7 154 66 0.90 0.12 13 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 9) 201 Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/I) (mg/1) 44 94 3 7 1545 31.3 140 6.4 1.60 0.15 72 28 94 3 7 1650 29.7 142 6.5 0.90 0.15 1 18 94 3 7 1745 29.6 145 6.5 1.60 0.16 7 16 94 3 7 1820 29.2 127 5.8 0.80 0.02 19 33 94 3 8 1125 31.0 159 5.9 1.30 0.12 0 31 94 3 8 1230 34.0 211 0.9 0.07 17 32 94 3 8 1310 33.9 142 2.1 0.06 22 37 94 3 8 1335 33.9 113 7.5 0.50 0.13 22 11 94 3 8 1430 33.3 7.49 118 7.1 0.90 0.07 10 7 94 3 8 1550 32.2 125 8.1 0.70 0.04 5 8 94 3 8 1625 31.0 7.07 92 6.3 0.70 0.01 4 10 94 3 8 1640 33.0 7.29 154 5.5 1.20 0.14 24 45 94 3 9 1105 31.9 7.51 291 6.9 0.90 0.11 8 50 94 3 9 1145 30.9 7.36 311 4.4 0.50 0.03 566 52 94 3 9 1210 32.5 7.35 178 6.4 1.50 0.04 14 48 94 3 9 1235 31.6 7.37 226 7.2 1.40 0.53 15 46 94 3 9 1250 30.9 7.24 173 6.0 1.90 2.27 10 19 94 3 9 1440 33.7 7.39 102 6.4 2.40 0.10 1 21 94 3 9 1515 32.6 7.17 102 7.1 1.00 0.15 8 17 94 3 9 1635 31.8 7.54 149 6.2 1.90 0.12 20 16 94 3 12 940 27.7 97 6.2 0.70 0.07 6 39 94 3 12 1010 29.2 163 0.50 0.19 28 40 94 3 12 1100 30.0 144 6.0 0.40 0.20 16 57 94 3 12 1330 32.8 6.76 143 6.2 1.50 0.20 25 56 94 3 12 1425 33.1 6.68 305 6.4 0.90 0.29 15 53 94 3 12 1505 32.5 6.55 520 5.9 0.60 0.24 54 54 94 3 12 1530 31.0 6.89 340 7.4 0.80 0.24 30 55 94 3 12 1545 30.7 6.80 141 7.3 0.80 0.19 32 44 94 3 12 1625 31.6 6.92 141 5.9 0.70 0.23 14 28 94 3 12 1720 29.9 6.96 151 7.6 0.90 0.19 23 13 94 3 13 940 27.3 115 5.3 0.90 0.56 24 14 94 3 13 1000 27.4 7.74 109 1.4 0.19 33 21 94 3 13 1015 28.9 6.65 123 5.8 1.20 0.28 26 17 94 3 13 1040 28.1 6.57 137 6.6 1.30 0.22 99 18 94 3 13 1115 29.4 6.76 124 7.6 0.70 0.21 12 45 94 3 13 1225 31.0 6.83 212 7.0 0.80 0.17 20 48 94 3 13 1315 32.3 6.90 232 6.4 0.50 0.40 89 52 94 3 13 1345 33.4 7.01 163 5.7 1.00 0.13 32 21 94 3 13 1510 31.4 6.77 98 6.7 0.80 0.16 23 19 94 3 13 1545 30.5 6.58 99 6.9 0.60 0.15 5 7 94 3 14 1210 29.0 7.00 133 6.6 0.60 0.08 13 8 94 3 14 1240 28.5 7.22 153 6.7 0.50 0.06 11 10 94 3 14 1310 33.9 6.36 128 6.5 0.50 0.15 4 33 94 3 14 1515 30.2 6.90 167 7.0 0.30 0.10 19 31 94 3 14 1605 31.3 6.89 170 7.4 0.60 0.18 6 Appendix Table 2-la. Water quality data on the Pampanga river and its tributaries (cont.p 10) 202 Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (DegC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/I) 32 94 3 14 1645 31.6 6.86 151 6.7 0.50 0.12 21 36 94 3 14 1710 27.8 7.35 110 6.2 0.40 0.13 17 37 94 3 14 1720 29.1 6.95 109 5.8 1.00 0.11 3 11 94 3 14 1805 28.4 7.13 135 6.3 0.40 0.13 18 40 94 3 19 1135 0.40 0.19 12 39 94 3 19 1150 0.50 0.16 11 57 94 3 19 1420 0.70 0.18 30 56 94 3 19 1510 0.50 0.14 15 53 94 3 19 1555 1.60 0.21 21 54 94 3 19 1615 0.30 0.20 23 55 94 3 19 1625 0.60 0.08 14 44 94 3 19 1710 0.50 0.12 18 28 94 3 19 1750 0.50 0.14 9 45 94 3 20 1105 32.2 6.77 214 5.5 2.00 0.09 2 52 94 3 20 1220 32.0 7.03 163 6.8 0.40 0.05 14 48 94 3 20 1250 30.6 6.79 283 7.4 2.20 0.64 42 21 94 3 20 1430 30.7 6.52 98 6.6 1.20 0.06 4 18 94 3 20 1515 31.7 6.72 118 6.9 1.30 0.07 24 17 94 3 20 1545 30.4 6.75 133 7.7 2.00 0.09 12 16 94 3 20 1605 30.7 6.59 117 8.1 2.40 0.08 12 14 94 3 20 1625 29.7 6.75 105 7.1 1.00 0.07 17 13 94 3 20 1645 29.6 6.74 108 7.0 0.50 0.44 8 33 94 3 21 1030 29.1 6.69 168 6.4 0.30 0.10 16 31 94 3 21 1155 30.6 6.66 149 6.3 0.50 0.07 19 32 94 3 21 1225 32.5 6.02 152 8.1 0.40 0.07 17 36 94 3 21 1255 29.1 7.01 110 6.7 0.60 0.04 29 37 94 3 21 1305 31.6 6.17 113 6.3 0.90 0.06 10 11 94 3 21 1400 31.3 6.72 120 6.7 0.40 0.09 34 7 94 3 21 1525 30.0 6.06 132 8.2 0.50 0.05 44 8 94 3 21 1550 28.5 6.60 88 6.8 0.30 0.03 20 10 94 3 21 1620 31.8 6.39 143 6.0 0.70 0.10 18 6 94 3 23 926 28.8 6.90 102 9.0 1.00 0.16 34 57 94 3 25 1200 30.5 6.92 144 6.8 0.70 0.05 14 56 94 3 25 1304 30.4 6.77 132 6.5 0.10 0.14 25 53 94 3 25 1415 31.0 6.99 216 5.6 0.30 0.27 33 54 94 3 25 1435 30.2 6.96 270 7.8 0.30 0.15 20 55 94 3 25 1455 30.1 6.94 136 7.1 0.40 0.06 20 44 94 3 25 1530 29.9 6.96 441 6.0 1.00 0.43 166 28 94 3 '25 1636 29.0 6.83 122 8.1 0.60 0.15 23 18 94 3 25 1705 29.0 6.93 119 6.1 3.20 0.11 8 16 94 3 25 1745 28.5 6.92 115 7.8 2.10 0.07 14 33 94 3 26 1105 27.9 6.97 156 6.6 0.80 0.10 18 31 94 3 26 1200 30.7 6.90 285 6.7 0.50 0.06 45 37 94 3 26 1305 30.3 6.88 116 5.7 1.00 0.08 16 11 94 3 26 1400 32.5 6.91 170 6.2 0.60 0.08 11 203 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 11) Station year month day time Temp p H TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 7 94 3 26 1525 28.5 6.84 139 6.2 0.50 0.06 2 8 94 3 26 1555 27:9 6.89 100 5.7 0.60 0.04 6 10 94 3 26 1625 30.6 6.89 144 6.6 0.90 0.22 5 45 94 3 27 1100 29.1 6.92 258 7.4 0.40 0.12 17 52 94 3 27 1155 29.7 6.94 168 6.8 0.40 0.10 28 48 94 3 27 1225 29.7 6.82 283 7.5 0.60 0.35 39 19 94 3 27 1505 28.7 6.90 79 6.0 0.80 0.12 24 21 94 3 27 1530 28.4 6.98 155 6.8 0.30 0.14 24 27 94 3 27 1610 28.5 6.90 91 6.0 0.20 0.06 63 17 94 3 27 1640 28.6 6.94 160 6.7 1.00 0.14 17 14 94 3 27 1700 27.7 6.94 110 6.7 0.50 0.03 14 13 94 3 28 1000 26.9 6.99 158 6.0 0.40 0.63 18 16 94 3 28 1025 27.1 6.94 111 5.9 0.40 0.02 78 42 94 3 28 1420 33.1 6.90 280 5.5 0.30 0.28 61 40 94 3 28 1550 31.2 6.94 139 6.7 0.60 0.10 23 39 94 3 28 1655 29.2 6.92 129 6.8 1.00 0.08 14 16 94 3 28 1750 26.8 6.92 102 6.9 1.10 0.03 12 39 94 4 7 1025 29.3 6.97 138 5.7 0.50 0.13 27 40 94 4 7 1105 29.7 6.95 130 6.2 0.10 0.16 21 57 94 4 7 1355 32.5 6.97 143 6.3 0.30 0.04 53 56 94 4 7 1440 30.7 6.91 267 6.1 0.30 0.10 24 53 94 4 7 1530 31.4 6.96 177 5.9 0.20 0.17 39 54 94 4 7 1600 31.7 6.94 186 5.5 0.40 0.15 37 55 94 4 7 1615 30.5 6.90 164 6.0 1.90 0.15 28 44 94 4 7 1705 30.7 6.90 131 6.1 0.40 0.14 33 28 94 4 7 1800 31.3 6.98 118 5.7 0.50 0.18 27 45 94 4 8 1150 31.3 6.95 252 6.8 3.90 0.04 25 52 94 4 8 1305 33.1 6.95 155 6.9 0.70 0.02 33 48 94 4 8 1340 29.3 7.06 112 5.8 0.80 0.83 51 21 94 4 8 1500 30.5 6.87 95 7.0 0.40 0.10 22 27 94 4 8 1535 31.2 6.85 109 6.7 0.50 0.03 20 18 94 4 8 1605 30.0 6.91 124 5.7 1.70 0.07 28 17 94 4 8 1635 29.1 6.94 131 5.7 1.00 0.04 27 16 94 4 8 1700 29.4 6.91 120 5.7 1.20 0.10 25 14 94 4 8 1720 28.8 6.97 120 5.7 0.30 0.09 26 13 94 4 8 1805 29.1 6.96 108 5.7 0.70 0.18 32 33 94 4 9 1030 28.5 6.88 191 5.8 1.10 0.14 15 31 94 4 9 1120 31.7 6.94 188 5.0 0.60 0.04 27 32 94 4 9 1155 30.2 6.95 129 5.5 0.50 0.06 29 36 94 4 9 1220 27.8 6.98 94 6.0 1.80 0.01 27 37 94 4 9 1230 31.7 6.86 111 5.0 0.60 0.09 25 11 94 4 9 1330 31.2 6.94 116 6.9 1.00 0.05 34 8 94 4 9 1500 28.7 6.91 98 6.1 0.50 0.02 15 7 94 4 9 1525 28.2 6.92 141 6.4 0.50 0.03 17 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 12) 204 Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/I) (mg/1) (mg/I) (mg/1) 10 94 4 9 1610 29.6 6.92 125 5.8 0.80 0.05 14 4 94 4 10 1200 27.2 6.96 51 7.3 0.40 0.03 12 39 94 4 17 1055 30.9 6.98 154 5.5 0.60 0.21 37 57 94 4 17 1325 31.4 6.96 135 6.0 0.40 0.14 34 56 94 4 17 1420 30.7 6.92 139 6.2 0.20 0.23 50 53 94 4 17 1510 31.0 6.96 152 5.7 0.50 0.22 31 54 94 4 17 1535 30.4 6.94 158 5.9 0.30 0.20 27 55 94 4 17 1555 30.0 6.91 169 6.4 0.40 0.23 31 44 94 4 17 1635 30.7 6.92 144 6.7 0.50 0.14 20 28 94 4 17 1735 29.9 6.87 136 . 7.1 0.60 0.14 20 45 94 4 18 1105 31.8 6.97 256 5.8 0.30 0.09 33 52 94 4 18 1210 33.1 6.95 157 5.8 0.40 0.07 41 48 94 4 18 1235 31.8 6.90 210 5.6 1.00 0.30 35 19 94 4 18 1420 31.7 6.88 97 7.0 0.80 0.08 11 21 94 4 18 1455 30.3 6.88 93 7.7 0.40 0.07 23 27 94 4 18 1535 32.0 6.86 101 7.3 0.20 0.08 16 18 94 4 18 1555 31.6 6.89 137 7.1 0.30 0.16 17 16 94 4 18 1805 30.9 6.94 130 6.2 0.70 0.19 13 14 94 4 18 1825 29.8 6.98 116 7.4 0.10 0.16 20 7 94 4 19 1100 28.9 6.90 185 7.6 1.10 0.20 13 8 94 4 19 1140 29.4 6.95 108 7.3 0.80 0.03 14 33 94 4 19 1405 33.5 6.87 171 5.5 0.70 0.13 28 31 94 4 19 1505 34.3 6.88 149 6.9 0.80 0.06 23 32 94 4 19 1545 35.4 6.88 146 7.0 0.80 0.05 15 37 94 4 19 1620 34.6 6.86 128 6.0 1.20 0.10 20 11 94 4 19 1710 32.5 6.94 133 6.0 0.50 0.12 25 39 94 4 29 1030 30.0 6.94 120 5.0 0.50 0.18 30 57 94 4 29 1306 32.3 6.96 179 5.6 0.50 0.32 47 56 94 4 29 1355 31.4 6.90 132 6.7 0.50 0.17 44 53 94 4 29 1405 30.8 6.94 171 4.1 0.30 0.28 36 54 94 4 29 1500 29.9 6.95 175 4.8 1.80 0.27 40 55 94 4 29 1510 29.9 6.91 130 6.4 0.80 0.21 37 44 94 4 29 1555 29.6 6.91 127 6.0 0.90 0.20 34 28 94 4 29 1705 29.6 6.89 132 6.1 0.60 0.17 17 45 94 4 30 1125 32.2 6.96 262 5.0 11 52 94 4 30 1230 33.4 6.98 173 5.2 0.80 0.12 67 48 94 4 30 1300 32.1 6.90 215 5.0 0.60 1.88 43 19 94 4 30 1435 34.1 6.86 98 7.1 0.60 0.18 7 21 94 4 30 1505 32,1 6.89 96 6.2 1.10 0.07 15 18 94 5 1 955 31.1 6.95 152 5.7 0.80 0.19 10 17 94 5 1 1020 30.4 8.98 149 5.5 0.70 0.13 86 16 94 5 1 1045 31.3 6.95 197 6.0 1.80 0.20 31 14 94 5 1 1100 29.8 6.99 154 6.5 0.70 0.20 38 13 94 5 1 1120 32.0 6.90 251 4.9 1.60 2.73 87 205 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 13) Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 33 94 5 1 1310 34.1 6.87 169 6.5 1.10 0.11 23 31 94 5 1 1405 34.8 6.90 157 6.2 1.20 0.09 91 32 94 5 1 1445 34.2 6.89 150 6.4 0.60 0.09 19 36 94 5 1 1510 31.0 6.80 123 6.0 0.20 0.12 29 37 94 5 1 1520 34.7 6.84 145 5.7 0.60 0.13 19 11 94 5 1 1610 32.6 6.95 126 6.2 0.80 0.13 21 39 94 5 14 1115 32.9 6.98 176 5.9 0.40 0.29 34 43 94 5 14 1230 38.2 6.87 400 4.5 0.10 0.57 638 57 94 5 14 1420 33.6 6.99 195 6.1 0.10 0.34 47 56 94 5 14 1525 30.9 6.89 178 8.3 0.10 0.40 80 54 94 5 14 1625 29.9 6.92 173 5.5 0.40 0.49 43 55 94 5 14 1640 30.2 6.97 163 6.1 0.20 0.39 100 44 94 5 14 1730 29.9 6.96 146 5.0 0.10 0.39 90 28 94 5 14 1830 30.4 6.96 147 5.4 0.10 0.25 21 45 94 5 15 1130 32.9 6.97 229 5.6 0.80 0.04 21 49 94 5 15 1225 31.9 6.51 122 5.0 0.30 0.06 37 50 94 5 15 1240 32.0 6.55 96 5.5 0.90 0.19 45 52 94 5 15 1305 32.7 6.94 180 5.5 0.30 0.24 29 48 94 5 15 1330 32.6 6.84 130 7.6 0.80 0.17 33 46 94 5 15 1355 32.1 6.98 237 5.0 1.90 2.75 53 21 94 5 15 1505 34.6 6.94 110 6.6 0.20 0.15 38 27 94 5 15 1545 35.8 6.92 115 5.4 1.10 0.05 10 18 94 5 15 1610 33.8 6.94 150 6.2 0.40 0.17 16 17 94 5 15 1640 32.9 6.96 187 6.4 0.50 0.20 23 16 94 5 15 1710 32.6 6.92 142 6.4 0.70 0.15 8 33 94 5 16 1225 33.8 6.92 171 5.8 0.80 0.20 16 31 94 5 16 1325 33.6 6.94 189 5.5 0.50 0.21 36 32 94 5 16 1400 34.9 6.96 171 5.7 0.80 0.31 10 37 94 5 16 1445 35.2 • 6.89 176 5.8 0.60 0.14 18 11 94 5 16 1505 34.1 6.97 147 5.5 0.70 0.16 27 11 94 5 27 905 29.4 6.99 183 6.1 1.80 0.08 15 37 94 5 27 945 30.5 6.98 176 5.9 1.00 0.19 21 32 94 5 27 1010 30.5 6.98 178 6.6 0.50 0.23 16 42 94 5 27 1440 33.7 6.93 309 5.4 0.40 0.68 40 39 94 5 27 1635 31.3 6.99 139 5.5 0.90 0.24 28 16 94 5 27 1725 31.2 6.97 156 5.4 0.40 0.24 24 14 94 5 27 1750 29.7 6.94 149 5.6 0.60 0.15 36 46 94 5 28 840 28.7 6.99 480 3.9 0.70 4.58 89 45 94 5 28 910 29.4 6.74 165 6.5 0.90 0.12 12 48 94 5 28 945 31.0 6.97 143 6.2 0.40 0.43 27 50 94 5 28 1000 29.8 6.93 106 5.5 0.10 0.19 71 52 94 5 28 1030 31.3 6.95 208 6.0 0.10 0.11 24 57 94 5 28 1130 31.6 6.58 286 5.1 0.10 0.51 42 56 94 5 28 1240 32.0 6.79 155 5.5 0.40 0.89 39 206 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 14) Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DegC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 53 94 5 28 1325 32.9 6.73 312 4.8 0.40 0.29 51 54 94 5 28 1355 31.5 6.86 303 5.5 0.10 0.75 58 55 94 5 28 1405 31.2 6.94 192 6.0 0.10 0.35 38 44 94 5 28 1430 32.4 6.98 177 5.9 0.70 0.29 24 28 94 5 28 1535 33.0 6.94 155 6.2 0.70 0.25 24 27 94 5 28 1620 33.5 6.90 140 7.4 1.50 1.15 16 18 94 5 28 1645 32.2 6.91 156 7.6 0.50 0.20 20 17 94 5 28 1715 32.0 6.96 202 6.0 0.30 0.14 26 7 94 6 4 845 27.3 6.93 181 7.7 0.60 0.09 14 8 94 6 4 915 29.0 6.93 138 5.8 0.60 0.12 17 10 94 6 4 1005 29.2 6.59 90 5.6 0.13 32 11 94 6 4 1035 29.9 6.86 156 6.2 0.20 0.17 23 37 94 6 4 1110 31.4 6.92 174 6.2 1.10 0.07 18 32 94 6 4 1135 31.7 6.93 187 7.0 0.70 0.10 15 30 94 6 4 1200 31.8 6.91 125 5.0 0.10 0.39 32 42 94 6 4 1430 29.1 6.96 370 4.4 0.30 0.50 54 43 94 6 4 1515 28.4 6.54 600 4.2 0.40 0.58 160 39 94 6 4 1600 30.1 6.92 191 6.4 0.40 0.19 25 16 94 6 4 1710 29.4 6.97 141 6.0 0.20 0.21 31 45 94 6 7 1020 29.8 6.54 204 6.4 0.90 0.10 14 48 94 6 7 1055 30.0 6.82 170 6.2 0.40 2.13 35 49 94 6 7 1115 29.2 6.60 108 5.6 0.10 0.03 37 50 94 6 7 1125 29.7 6.58 64 5.5 0.60 0.03 64 52 94 6 7 1155 30.7 6.81 129 5.3 0.40 0.04 31 57 94 6 7 1325 32.0 6.99 253 5.2 0.30 0.34 52 56 94 6 7 1415 30.7 6.96 241 6.0 1.00 0.27 45 54 94 6 7 1510 31.6 6.93 470 5.4 0.40 1.31 45 55 94 6 7 1525 30.2 6.98 187 6.1 0.10 0.33 69 44 94 6 7 1620 30.1 6.98 150 5.0 0.10 0.40 60 28 94 6 7 1705 30.0 6.91 119 6.2 0.40 0.24 32 27 94 6 7 1745 31.7 6.90 129 6.5 0.60 0.12 13 18 94 6 7 1810 29.8 6.96 121 5.5 0.80 0.21 35 45 94 6 12 920 28.8 6.71 130 5.8 0.10 0.20 34 48 94 6 12 950 30.0 6.89 150 4.5 0.30 0.43 19 49 94 6 12 1010 29.4 6.92 123 6.2 0.10 0.01 23 50 94 6 12 1025 29.2 6.77 120 5.5 0.10 0.01 65 52 94 6 12 1045 30.3 6.84 151 5.5 1.70 0.14 15 57 94 6 12 1150 30.9 6.85 216 4.9 1.10 0.38 34 56 94 6 12 1305 31.3 6.94 150 5.6 0.40 0.35 32 54 94 6 12 1345 31.8 6.62 194 5.5 0.40 0.63 44 55 94 6 12 1400 30.9 6.96 162 5.7 0.30 0.26 27 44 94 6 12 1440 32.0 6.95 163 5.5 0.40 0.30 25 28 94 6 12 1535 31.3 6.93 161 5.7 0.50 0.26 16 27 94 6 12 1620 32.2 6.89 192 5.4 0.70 0.12 17 207 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 15) Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 17 94 6 12 1700 30.7 6.96 186 4.9 0.30 0.16 17 16 94 6 12 1715 30.8 6.95 203 5.9 0.50 0.32 19 14 94 6 12 1730 30.4 6.99 159 5.8 0.10 0.15 58 7 94 6 16 830 29.2 6.71 186 6.2 0.90 0.11 12 8 94 6 16 910 29.2 .6.92 184 6.2 0.70 0.08 21 10 94 6 16 950 31.3 6.97 138 5.7 0.50 0.04 30 13 94 6 16 1025 30.4 6.64 165 5.7 0.60 0.60 38 16 94 6 16 1045 31.4 6.98 151 5.9 0.60 0.16 20 39 94 6 16 1130 32.7 6.99 194 5.2 0.60 0.29 17 43 94 6 16 1230 36.5 6.89 730 4.8 0.90 0.53 238 42 94 6 16 1330 35.2 6.93 310 4.7 0.40 0.58 24 30 94 6 16 1535 33.2 6.87 131 5.5 2.60 0.53 56 32 94 6 16 1610 32.0 6.99 194 5.3 0.60 0.15 6 37 94 6 16 1650 31.3 6.95 115 5.7 0.80 0.07 13 11 94 6 16 1725 31.0 6.96 149 5.8 0.60 0.13 6 45 94 6 17 800 29.0 6.89 206 5.7 0.70 0.15 15 48 94 6 17 855 30.4 6.97 183 5.3 0.60 0.49 20 49 94 6 17 920 29.6 6.99 175 5.1 0.60 0.06 19 50 94 6 17 930 28.9 6.78 107 5.4 0.10 0.11 21 52 94 6 17 955 30.6 6.98 155 4.8 0.50 0.06 21 57 94 6 17 1055 30.0 6.94 187 5.5 0.20 0.31 38 56 94 6 17 1145 31.3 6.98 183 5.6 0.50 0.34 28 54 94 6 17 1300 32.0 6.81 225 4.8 0.40 0.87 42 55 94 6 17 1320 31.9 6.97 176 5.9 0.90 0.30 26 44 94 6 17 1400 32.0 6.93 193 5.5 0.80 0.21 23 28 94 6 17 1455 32.0 6.91 142 6.0 1.20 0.16 21 18 94 6 17 1510 31.9 6.91 156 5.9 0.40 0.14 14 27 94 6 17 1550 32.0 6.95 115 5.3 0.50 0.10 23 17 94 6 17 1610 31.7 6.95 179 5.3 0.50 0.15 19 16 94 6 17 1630 31.4 6.91 158 6.4 0.30 0.16 16 7 94 6 18 820 28.0 6.83 160 5.5 0.60 0.13 18 8 94 6 18 855 28.9 6.99 159 6.2 0.70 0.09 24 10 94 6 18 930 29.7 6.97 112 5.5 0.30 0.07 28 13 94 6 18 1030 30.2 6.76 213 4.8 0.80 1.64 47 14 94 6 18 1040 29.4 6.94 197 5.8 0.80 0.10 36 16 94 6 18 1055 30.4 6.95 154 5.7 0.80 0.20 13 39 94 6 18 1135 30.9 6.99 121 5.3 0.10 0.13 33 43 94 6 18 1250 32.8 6.92 710 4.9 0.70 0.47 51 42 94 6 18 1345 33.9 6.91 312 4.6 0.50 0.59 58 30 94 6 18 1555 31.7 6.79 132 6.1 0.10 0.19 34 32 94 6 18 1630 31.5 6.98 147 5.4 0.50 0.11 25 37 94 6 18 1700 31.3 6.89 179 5.9 0.30 0.13 15 11 94 6 18 1735 31.4 6.92 164 5.3 0.50 0.14 14 45 94 6 24 910 26.9 6.65 142 6.1 0.80 0.05 18 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 16) 208 Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DegC) units (ppm) (mg/1) (mg/1) (mg/1) (mg/1) 48 94 6 24 940 26.8 6.51 82 6.0 0.40 0.13 17 49 94 6 24 1000 26.7 6.65 62 5.9 0.10 0.10 27 50 94 6 24 1010 27.6 6.76 68 6.1 0.30 0.01 30 52 94 6 24 1040 26.5 6.60 71 6.2 0.20 0.01 24 57 94 6 24 1145 28.9 6.56 148 5.9 0.10 0.17 36 56 94 6 24 1255 28.4 6.58 189 5.0 0.10 0.19 242 54 94 6 24 1330 28.9 6.46 60 5.3 0.10 0.03 31 55 94 6 24 1345 27.7 6.88 165 6.0 0.10 0.28 333 44 94 6 24 1430 28.4 6.70 153 6.2 0.10 0.05 161 18 94 6 24 1535 30.5 6.99 130 5.8 0.50 0.22 33 28 94 6 24 1555 30.4 6.97 122 5.9 0.50 0.15 29 27 94 6 24 1630 29.6 6.98 86 6.2 0.50 0.14 29 17 94 6 24 1655 29.2 6.99 115 5.8 0.90 0.13 27 16 94 6 24 1715 29.4 6.97 124 6.0 0.30 0.12 39 7 94 6 25 830 26.7 6.90 155 5.8 1.30 0.07 17 8 94 6 25 900 28.9 6.99 130 5.8 0.70 0.11 8 10 94 6 25 930 29.1 6.95 133 5.7 0.30 0.17 22 16 94 6 25 1025 30.4 7.00 127 6.2 0.40 0.05 14 39 94 6 25 1115 29.8 6.89 128 5.8 0.40 0.23 22 43 94 6 25 1210 34.5 6.95 290 5.3 0.40 0.35 161 42 94 6 25 1320 32.1 6.99 207 5.7 0.10 0.38 73 30 94 6 25 1625 32.1 6.89 75 5.7 0.20 0.05 26 32 94 6 25 1645 32.6 6.98 141 5.5 0.40 0.12 18 45 94 7 11 1005 26.9 6.99 89 6.0 0.50 0.21 34 48 94 7 11 1045 27.0 6.87 103 6.0 0.30 0.28 34 49 94 7 11 1100 26.5 6.86 86 5.7 0.10 0.03 52 50 94 7 11 1115 27.6 6.71 60 4.3 0.25 0.10 48 52 94 7 11 1140 26.5 6.99 88 5.8 0.50 0.09 163 57 94 7 11 1245 27.5 6.99 162 5.3 0.30 0.33 54 56 94 7 11 1400 25.9 6.93 255 5.4 0.25 0.80 183 54 94 7 11 1440 26.0 6.90 154 5.5 0.40 0.41 45 55 94 7 11 1500 26.2 6.97 184 5.4 0.25 0.37 180 44 94 7 11 1535 26.1 6.97 147 5.5 0.25 0.62 81 28 94 7 11 1655 26.0 6.97 90 5.7 0.10 0.22 31 18 94 7 11 1720 26.0 6.98 91 6.0 0.10 0.20 28 16 94 7 11 1825 25.6 6.85 100 6.2 0.50 0.15 38 7 94 7 13 825 27.6 6.88 161 5.5 0.70 0.15 29 8 94 7 13 905 27.6 6.83 122 5.9 0.60 0.16 63 10 94 7 13 955 27.9 6.94 86 5.7 0.10 0.12 13 16 94 7 13 1100 29.0 6.80 116 6.2 0.20 0.15 26 39 94 7 13 1155 28.3 6.74 114 5.5 0.10 0.22 28 42 94 7 13 1335 30.7 6.99 330 5.7 0.30 0.27 51 30 94 7 13 1520 29.2 6.99 94 5.4 0.60 0.02 43 32 94 7 13 1555 30.2 6.97 127 6.2 0.10 0.09 15 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 17) 209 Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (DegC) units (PPm) (mg/1) (mg/1) (mg/1) (mg/1) 36 94 7 13 1630 29.7 6.71 93 5.5 0.10 0.10 33 37 94 7 13 1645 30,3 6.96 184 6.0 0.40 0.31 81 11 94 7 13 1735 28.9 6.98 128 6.2 0.80 0.25 28 57 94 7 15 950 29.0 6.88 163 5.5 0.10 0.10 58 56 94 7 15 1040 29.2 6.83 125 5.3 0.50 0.22 63 54 94 7 15 1120 29.8 6.81 127 4.3 0.30 0.20 26 55 94 7 15 1135 29.3 6.94 141 5.6 0.10 0.35 58 44 94 7 15 1215 29.4 6.89 136 5.5 0.10 0.30 42 28 94 7 15 1340 29.6 6.98 128 5.7 0.20 0.19 8 18 94 7 15 1400 29.3 6.99 122 6.2 0.20 0.19 7 27 94 7 15 1440 29.9 6.95 127 6.0 0.40 0.24 15 17 94 7 15 1505 28.5 6.96 125 5.9 0.20 0.11 25 16 94 7 15 1530 28.8 6.99 127 6.0 0.40 0.24 12 14 94 7 15 1550 28.5 6.92 121 5.0 0.50 0.07 26 12 94 7 16 730 25.6 6.33 108 3.6 0.10 2.75 30 13 94 7 16 750 26.0 6.70 92 4.0 0.30 0.66 35 49 94 7 16 900 26.6 6.91 160 6.0 0.40 0.22 51 50 94 7 16 910 26.1 6.65 63 5.3 0.30 0.36 52 51 94 7 16 925 26.7 6.51 74 4.5 0.30 0.26 37 52 94 7 16 955 26.9 6.99 115 5.7 0.70 0.20 10 48 94 7 16 1020 26.6 6.99 135 6.0 1.80 0.26 1 45 94 7 16 1055 27.8 6.98 106 6.2 0.90 0.29 73 46 94 7 16 1130 27.6 6.75 116 4.7 0.60 1.88 49 21 94 7 16 1300 28.7 6.98 108 6.0 0.90 0.19 2 16 94 7 16 1355 29.4 6.69 96 5.5 0.30 0.28 7 94 7 18 800 26.4 6.99 157 6.0 1.20 0.22 6 8 94 7 18 835 27.1 6.99 189 6.0 0.80 0.22 55 10 94 7 18 910 27.3 6.94 113 6.1 0.50 0.16 41 16 94 7 18 1010 27.3 6.99 124 5.3 0.60 0.14 37 39 94 7 18 1015 27.7 6.82 116 5.3 0.10 0.33 36 43 94 7 18 1155 25.1 6.79 325 5.8 0.20 0.29 117 42 94 7 18 1325 23.8 6.66 168 5.8 0.10 0.47 158 30 94 7 18 1525 26.9 6.91 95 4.8 0.10 0.14 62 32 94 7 18 1600 26.3 6.97 135 5.0 0.30 0.20 34 36 94 7 18 1630 26.3 6.85 91 5.6 0.60 0.06 49 37 94 7 18 1640 26.0 6.96 154 5.7 0.80 0.18 2 11 94 7 18 1725 26.4 6.97 119 5.3 0.80 0.12 0 57 94 7 19 1040 27.3 6.58 194 6.0 0.10 0.85 214 56 94 7 19 1125 27.3 6.73 149 5.5 0.10 0.31 133 54 94 7 19 1215 27.9 6.83 156 5.5 0.20 0.29 13 55 94 7 19 1230 27.2 6.74 129 5.3 0.60 0.33 100 44 94 7 19 1300 26.8 6.79 102 5.9 0.10 0.45 65 28 94 7 19 1420 27.4 6.56 71 6.0 0.10 0.05 52 18 94 7 19 1445 27.7 6.61 65 5.7 0.10 0.08 33 210 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 18) Station year month day time Temp pH TDS DO nitrate 0-PO4 COD Number (Deg C) units (ppm) (mg/0 (mg/1) (mg/1) (mg/1) 27 94 7 19 1520 27.2 6.81 62 6.0 0.10 0.54 32 17 94 7 19 1605 27.7 6.45 110 6.0 0.10 0.10 16 16 94 7 19 1625 26.6 6.69 64 6.0 0.10 0.09 45 14 94 7 19 1640 27.7 6.42 63 5.7 0.10 0.12 122 12 94 7 19 1720 28.6 6.71 65 4.1 0.30 0.86 35 46 94 7 21 855 27.0 6.77 89 5.3 0.10 0.94 21 49 94 7 21 915 28.0 6.82 130 6.2 0.10 0.18 14 50 94 7 21 925 27.9 6.60 52 5.5 0.10 0.12 45 51 94 7 21 . 940 28.6 6.52 75 5.3 0.20 0.08 29 52 94 7 21 1000 28.5 6.48 98 6.1 0.90 0.16 23 48 94 7 21 1025 27.7 6.79 128 6.0 0.40 0.28 8 45 94 7 21 1100 28.9 6.88 95 6.2 0.70 0.26 6 21 94 7 21 1220 29.0 6.82 103 5.9 0.60 0.40 9 16 94 7 21 1340 30.2 6.72 74 5.7 0.10 0.20 62 13 94 7 21 1405 29.8 6.61 71 4.9 0.10 0.60 20 7 94 7 23 1000 27.2 6.90 117 6.0 0.60 0.21 7 8 94 7 23 1030 27.5 6.69 132 5.7 0.80 0.25 9 10 94 7 23 1110 27.9 6.99 99 6.0 0.40 0.23 19 16 94 7 23 1205 30.0 6.51 96 5.7 0.30 0.27 25 39 94 7 23 1230 30.2 6.67 89 5.9 0.20 0.28 20 43 94 7 23 1340 29.4 6.74 480 6.2 0.40 0.55 194 42 94 7 23 1445 27.9 6.82 301 5.5 0.40 0.45 58 30 94 7 23 1635 27.9 6.99 97 5.4 0.10 0.35 27 32 94 7 23 1705 28.2 6.97 141 5.8 0.90 0.28 23 36 94 7 23 1735 27.9 6.63 101 5.7 0.10 0.22 4 37 94 7 23 1750 27.8 6.96 143 6.0 0.10 0.48 21 11 94 7 23 1820 26.9 6.98 105 6.0 1.00 0.34 0 57 94 7 24 1030 28.2 6.82 96 5.3 0.10 2.21 3 56 94 7 24 1120 28.7 6.67 105 5.0 0.10 0.55 11 54 94 7 24 1155 30.1 6.59 77 6.1 0.80 0.20 0 55 94 7 24 1200 29.3 6.50 128 5.5 0.10 0.42 43 44 94 7 24 1245 30.2 6.51 110 6.2 0.10 0.54 28 28 94 7 24 1400 28,5 6.70 98 6.0 0.10 0.32 10 18 94 7 24 1420 28.9 6.70 90 6.2 0.10 0.16 0 17 94 7 24 1450 28.5 6.64 65 6.1 0.10 0.08 0 16 94 7 24 1515 . 29.7 6.72 93 61 0.20 0.28 1 14 94 7 24 1525 28.9 6.58 75 6.2 0.10 0.11 1 13 94 7 24 1535 28.4 6.61 86 5.3 0.10 0.83 5 12 94 7 24 1600 30.4 6.77 106 6.2 0.10 1.55 9 16 94 7 25 800 27.2 6.89 112 6.0 0.10 0.24 28 46 94 7 25 950 28.6 6.50 87 5.4 0.10 1.46 36 45 94 7 25 1020 27.5 6.90 88 5.9 0.70 0.21 16 48 94 7 25 1050 27.9 6.71 101 6.0 0.30 0.18 39 49 94 7 25 1105 27.7 6.88 132 5.9 0.10 0.04 31 211 Appendix Table 2- la. Water quality data on the Pampanga river and its tributaries (cont.p 19) Station year month day time Temp pH TDS DO nitrate 0-P04 COD Number (Dcg C) units (ppm) (mg/1) (mg/1) (mg/1) (mg/I) 50 94 7 25 1110 28.5 6.42 70 5.6 0.10 0.41 40 51 94 7 25 1125 24.0 6.84 66 6.2 0.10 1.19 52 52 94 7 25 1140 27.0 6.53 72 5.9 0.10 0.12 26 21 94 7 25 1330 27.0 6.92 130 5.6 0.50 0.26 38 27 94 7 25 1410 26.7 6.99 138 5.7 0.80 0.40 9 8 94 7 27 850 25.5 6.18 116 6.0 0.10 0.19 33 10 94 7 27 930 26.0 6.87 79 6.0 0.50 0.42 38 16 94 7 27 1110 27.5 6.71 74 6.2 0.10 0.14 26 39 94 7 27 1150 28.0 6.66 103 5.0 0.10 0.27 43 43 94 7 27 1245 30.6 6.74 380 6.0 0.40 0.41 93 42 94 7 27 1400 28.0 6.76 340 5.7 0.50 0.29 36 30 94 7 27 1550 27.0 6.66 123 6.2 0.10 0.22 36 32 94 7 27 1615 27.1 6.96 107 5.6 0.10 0.20 44 36 94 7 27 1645 27.2 6.73 77 5.5 0.20 0.03 43 37 94 7 27 1650 27.1 6.96 125 6.0 0.30 0.34 49 11 94 7 27 1720 26.7 6.77 102 5.9 0.20 0.18 36 27 94 7 28 735 26.1 6.99 92 6.0 1.30 1.60 112 46 94 7 28 810 27.9 6.75 129 4.8 0.20 0.18 25 45 94 7 28 840 26.4 6.97 105 5.7 0.80 0.10 13 48 94 7 28 905 26.6 6.91 122 6.0 1.00 0.16 12 49 94 7 28 915 27.0 6.90 112 5.5 0.60 0.07 25 50 94 7 28 925 27.1 6.92 55 5.5 0.30 0.23 52 94 7 28 940 27.2 6.87 110 6.2 0.60 0.14 5 57 94 7 28 1040 27.4 6.75 103 5.3 0.40 0.29 36 56 94 7 28 1155 27.0 6.75 119 6.1 0.50 0.33 33 54 94 7 28 1225 27.3 6.81 87 4.4 0.10 0.24 17 55 94 7 28 1240 27.3 6.91 110 5.0 0.10 0.26 28 94 7 28 1715 26.8 6.69 58 6.2 3.00 0.07 109 18 94 7 28 1730 26.2 6.42 142 6.1 0.10 0.02 67 16 94 7 28 1800 26.2 6.70 73 6.0 3.00 0.02 40 12 94 7 28 1825 27.7 6.73 105 3.9 0.10 1.53 54 212 Appendix 2-2a :Personal Communications M. Ballesteros J. Cabanayan, Jr. Chief, EQD-EMPAS, DENR-Central Luzon San Fernando, Pampanga Chief, Land Classification Division NAMRIA, DENR Fort Bonifacio, Makati R. Cordero G. Ferrer D. Gamboa H. Hernando R. Lope R. Mercado L. Paet W. Penetrante E. Pinlac Project Coordinator, Nueva Ecija Land-use Plan CARPO, Talavera, D A R North Talavera, Nueva Ecija PPDC and Deputy Project Director, IDP/NE Cabanatuan City, Nueva Ecija Chemist EQD, EMPAS, DENR-Central Luzon San Fernando, Pampanga Water Specialist, PAGASA PRB Flood Forecasting Unit Diliman, Quezon City Forester Forest Resources Section, CENRO- Cabanatuan Cabanatuan City Regional Director N E D A - Central Luzon San Fernanado, Pampanga Regional Technical Director-EMPAS-DENR-Central Luzon San Fernando Pampanga Engineer, Water Allocation Division UPRP, Cabanatuan, Nueva Ecija Water Resources Engineer E M B - D E N R Diliman, Quezon City E. Serote Professor UP-SURP Diliman, Quezon City Appendix 2-2a :Personal Communications (cont... p.2.) E. Tolentino R. Umipig P. Vergara E. Zalun Chief Engineer, DRD Pantabangan Reservoir Pantabangan, Nueva Ecija PPDO, IDP/NE Cabanatuan City, Nueva Ecija Provincial Veterinarian, Province ofTarlac Tarlac, Tarlac DOTI Representative to PLUC DOTI-Nueva Ecija Cabanatuan, Nueva Ecija Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaCQ3/l) (mg CaCQ3/l) 7 86/11/30 8 248.5 . 169.21 7 86/11/30 7.15 . 7 86/11/30 7.48 . 20 16 7 87/02/12 7.45 400 180 185 7 87/04/24 6.82 352 130 200 7 87/05/20 7.32 240 80 150 7 87/07/22 7.34 368 195 175 7 87/09/16 6.64 304 300 140 7 87/10/28 6.73 406.4 50 230 7 89/07/27 7.32 367.2 150 . 7 89/08/30 7.94 . 130 . 7 89/10/06 8.15 . 7 89/11/25 7.75 . 7 89/12/28 7.85 . 7 90/06/20 7.99 263 . 144.4 7 90/07/10 7.08 175 . 95 7 90/08/10 7.9 300 . 135.72 7 90/09/07 7.73 196 . 120 7 91/11/07 6.4 120.6 210 170 7 92/01/15 6.4 146 280 190 7 92/02/20 7 163.4 260 120 7 92/04/15 6.8 154 560 220 7 92/05/18 7 171 270 120 7 93/03/09 7 151 240 250 7 93/05/18 146.7 140 180 7 93/10/15 165.8 286 200 7 93/11/18 156.3 30 140 7 94/01/01 129.6 80 50 7 94/02/01 122.8 . 134.9 7 94/03/01 120 . 131.1 7 94/04/01 151.3 . 142.5 10 86/06/07 7.8 . 10 86/06/07 7.95 212.1 . 106.63 10 86/06/07 147.2 . 10 86/06/07 240 152.5 10 86/11/30 7.75 . 14.5 17 10 87/02/12 6.29 368 140 220 10 87/04/24 7.64 304 170 210 10 87/05/20 7.42 320 120 140 10 87/07/16 6.39 144 85 125 10 87/10/28 6.72 368 110 150 10 89/07/27 7.64 198.4 110 . 10 89/08/30 7.84 . 320 . 10 89/10/06 8.02 . 10 89/11/25 7.33 . 10 89/12/27 3.78 . 10 90/03/28 Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont.p. 2) Station Date Taken p H TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaCQ3/l) (mg CaCQ3 / l) 10 90/06/20 7.06 185.5 . 119.76 10 90/07/10 7.54 168 . 102.6 10 90/08/09 7.74 . 121.8 10 90/09/07 7.57 178.5 . 118 10 91/11/07 6.85 144.4 210 200 10 92/01/15 6.4 135 200 230 10 92/02/20 7.2 134 180 200 10 93/03/09 6 83 110 200 10 93/10/15 116 190 280 10 93/11/18 139 140 140 10 94/01/01 142.5 60 100 10 94/02/01 122.9 . 45.6 10 94/03/01 140 . 146.3 10 94/04/01 150 . 129.2 11 86/12/01 7.74 240.1 155.31 . 11 86/12/01 7.53 . 11 86/12/01 7.71 . 15.5 18 11 87.07/24 6.85 320 130 140 11 87/04/23 7.6 272 150 140 11 87/05/22 7.23 294.4 190 130 11 87/09/18 6.59 163.2 110 110 11 87/10/30 6.73 150 150 120 11 89/07/27 7.15 300.8 100 . 11 89/08/30 7.88 . 175 . 11 89/10/05 7.84 . 11 89/11/25 7.95 . 11 89/12/27 6.44 . 11 90/03/28 11 90/06/21 6.72 168 . 100.7 11 90/07/05 6.3 154 . 76 11 90/08/09 6.33 . 116.58 11 90/10/17 7.72 129.5 . 86 11 91/11/08 8 125 160 180 11 92/01/15 6.8 225 300 220 11 92/02/21 6.8 134.1 240 230 11 92/04/14 6 142 270 280 11 92/05/15 7 126 180 230 11 93/04/23 183.2 290 260 11 93/09/03 230 330 230 11 93/10/15 127.1 290 260 11 93/11/17 162.6 60 80 11 93/12/12 89.6 100 130 11 94/01/01 231 50 180 11 94/02/01 130 . 134.9 11 94/03/01 240 . 163.4 11 94/04/01 244 . 209 16 86/06/06 7.43 . Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont.p. 3) 216 Station Number Date Taken pH (pH units) TDS (ppm) Total hardness (mg CaC03/l) Total alkalinity (mg CaC03/l) 16 86/06/06 115 140 16 86/11/27 7.69 15 16.5 16 87/04/21 7.55 256 120 100 16 87/04/21 7.55 256 220 130 16 87/05/18 7.32 432 210 140 16 87/07/20 7.47 240 135 165 16 87/09/14 3.42 224 150 . 16 87/10/26 6.67 150 190 150 16 87/11/23 5.23 176 90 120 16 89/07/25 7.18 262.4 280 . 16 89/08/28 7.09 370 . 16 89/09/21 6.75 16 89/11/23 7 16 89/12/19 7.81 16 90/03/26 7.89 4 . 16 90/04/06 7.34 164.5 . 104 16 90/04/15 7.88 245 . 146.3 16 90/06/19 7.19 185 . 123.5 16 90/08/17 7.94 97.44 16 90/07/18 7.75 127.3 16 91/11/08 7 172.3 220 200 16 92/01/15 6.4 216 180 150 16 92/02/19 6.8 129 150 90 16 92/04/13 6.8 137 300 190 16 92/05/14 7 146 200 200 17 84/05/29 7.77 17 84/05/29 140.8 15.2 15.75 17 84/07/25 147.2 . 17 86/06/07 192.5 150 17 86/11/29 7.49 19.2 18 17 87/02/11 7.77 416 185 210 17 87/04/25 7.49 409.6 180 170 17 87/09/17 6.18 76.8 110 110 17 87/10/29 6.67 320 120 210 17 89/07/25 7.31 128 30 . 17 89/11/24 7.98 17 89/12/20 7.93 17 90/03/27 17 90/04/16 7.45 242.9 . 136.8 17 90/06/20 6.8 164.52 . 110.2 17 90/07/18 7.6 74.1 17 90/08/17 7.23 156.6 17 90/08/29 7.57. 95 . 17 90/09/06 7.07 192.5 . 136 17 91/11/07 7 139.1 180 210 17 92/01/14 6.8 185 260 220 17 92/02/20 6.8 162 190 320 Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont..p.4) 217 Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaC03/l) (mg CaC03/l) 17 92/04/15 6 145 220 290 17 92/05/18 7 155 290 290 17 93/03/05 139.7 170 200 17 93/09/01 5 82 140 130 17 93/10/15 113 200 190 17 93/11/18 152.4 110 210 17 93/12/15 158.5 110 110 17 94/01/01 164 100 90 17 94/02/01 114.8 . 150.1 17 94/03/01 120 . 123.5 18 84/05/28 134.4 11.5 12.25 18 84/07/26 192 . 18 87/02/11 7.89 368 145 160 18 87/02/11 7.88 368 150 140 18 87/02/12 7.91 400 165 230 18 87/02/17 7.86 432 150 175 19 86/06/07 7.9 220.5 . 106.63 19 86/06/07 7.91 19 84/05/29 147.2 14.5 16.5 19 84/07/26 185.6 . 19 86/06/07 260 217.5 19 86/11/29 7.64 28.3 20 19 87/02/11 7.97 400 205 245 19 87/04/25 7.56 352 160 160 19 87/05/21 7.36 345.3 230 140 19 87/07/23 7.37 288 145 240 19 87/09/17 6.88 249.6 210 160 19 87/10/29 6.2 432 150 140 19 89/07/25 7.46 217.6 90 . 19 89/08/29 7.2 200 . 19 89/11/24 7.91 19 89/12/20 7.28 50 . 19 90/03/27 1150 . 19 90/06/19 7.56 231 . 140.65 19 90/07/11 7.2 129.5 . 85.5 19 90/08/10 7.79 315 . 144.42 19 90/09/07 7.47 178.5 . 116 19 92/01/15 6.4 146 160 160 19 93/02/20 6.4 151 240 280 28 86/11/28 7.85 259 . 147.62 28 86/11/28 7.66 28 89/08/89 6.6 270 . 28 86/11/28 7.35 15.5 19 28 87/05/18 7.48 384 240 245 28 87/07/20 6.79 320 160 185 28 87/09/14 6.89 243.2 200 130 28 87/10/26 6.49 432 170 240 28 89/07/25 7.5 243 160 . Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont. p. 5) 218 Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaC03/I) (mg CaC03/l) 28 89/11/23 7.77 28 89/12/19 6.62 28 90/03/06 7.78 28 . 28 90/06/19 7.03 189 . 114 28 90/07/13 6.73 85.5 28 90/08/17 6.74 147.9 28 90/09/06 7.58 171.5 . 112 28 91/11/05 8 125.3 180 140 28 92/01/14 6.4 153 140 210 28 92/02/19 6.8 131 180 220 28 92/04/13 6.4 153 460 200 28 92/05/14 6 137 230 146 28 93/08/26 7 148 160 200 28 93/10/15 171.1 190 110 28 93/11/18 169.2 90 90 28 93/12/16 76.9 140 130 28 94/01/01 133.2 60 130 28 94/02/01 177.5 . 146.3 28 94/03/01 110 . 104.5 28 94/04/01 103.5 . 89.3 31 84/05/30 131.2 17 12.5 31 84/07/24 192 . 32 86/01/12 6.99 32 86/01/12 5.98 170 . 90.4 32 86/01/12 7.92 19 16 32 86/06/07 210 160 32 87/02/12 6.89 416 180 145 32 87/04/22 6.39 288 140 110 32 87/05/19 7.32 352 100 125 32 87/07/21 6.97 320 145 175 32 87/10/27 6.72 448 180 180 32 87/11/24 6.75 339.2 60 190 32 89/07/28 7.58 403.2 270 . 32 89/08/31 6.98 190 . 32 89/10/04 8.16 32 89/12/29 7.65 32 90/06/20 7.07 182 . 102.36 32 90/07/10 7.36 168 . 106.4 32 90/08/09 6.59 30.5 32 90/09/25 6.7 213.5 . 112 32 90/10/17 7.92 203 . 130 32 91/11/05 7.2 216 570 230 32 92/01/16 6.8 186 170 180 32 92/02/21 6.4 132 250 240 32 92/04/14 6 177 300 150 32 92/05/15 7 161 210 220 32 93/03/19 125.6 340 260 Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont. p. 6) 219 Station Date Taken PH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaC03/l) (mg CaC03/l) 32 93/09/02 7 152 150 100 32 93/10/27 145 70 210 32 93/11/17 180 80 170 32 93/12/16 137.7 220 216 32 94/01/01 162.8 80 140 32 94/02/01 160 . 133 32 94/04/01 166 . 226.1 33 86/06/07 7.98 33 84/05/30 140.8 18 17.5 33 84/07/22 79.36 . 33 86/06/07 187.5 150 33 86/12/02 7.77 30 16 33 87/04/22 7.59 416 180 172 33 87/05/19 7.36 368 220 160 33 87/07/02 7.63 400 185 230 33 87/10/27 4.25 192 70 52 33 87/11/24 5.99 332.8 190 160 33 89/07/28 7.69 288 110 . 33 89/08/31 7.27 125 . 33 89/J 0/04 7.17 33 89/12/29 7.63 33 90/04/18 8.12 284.9 . 163.4 33 90/06/21 7.68 238 . 146.03 33 90/07/05 6.28 94.5 . 49.4 33 90/08/09 7.51 116.58 33 90/09/25 7.57 182 . 80 33 90/10/17 7.96 199.5 . 131 33 94/01/01 161.8 120 90 33 94/02/01 170 . 165.3 33 94/04/01 190 . 171 37 91/11/07 6.4 168 200 360 37 92/01/17 6.8 184 230 200 37 92/02/21 6.8 176.5 220 290 37 92/04/14 6.8 203 370 260 37 92/05/15 7 178 230 190 37 93/03/19 171.9 180 310 37 93/09/02 7 161 210 160 37 93/10/27 137.6 100 120 37 93/1 1/17 143.8 120 60 37 93/12/12 140.4 90 165 39 86/11/27 7.67 39 86/! 1/27 7.33 17 15.5 39 87/02/11 7.69 334 130 250 39 87/04/21 6.99 416 170 160 39 87/07/24 6.55 352 150 150 39 87/09/19 239 110 110 39 87/10/30 352 110 140 Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways (cont..p.7) 220 Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaCQ3/l) (mg CaCQ3/l) 39 89/07/26 7.39 . 268.8 160 . 39 89/08/29 7.41 . 85. . 39 89/11/24 6.97 . 39 89/12/22 7.18 . 39 90/04/15 7.01 212.1 . 165.3 39 90/06/20 7.52 231 . 140.6 39 90/07/05 6.03 140 . 79.8 39 90/08/08 7.12 . 95.7 39 90/09/05 7.4 133 . 82 39 92/01/17 6.8 183 110 220 39 92/02/19 6.8 202 170 150 39 92/04/14 6 179 230 80 39 92/05/14 7 181 290 110 39 94/01/01 154.4 . 40 39 94/04/01 232 . 152 43 92/11/05 423 400 180 43 93/07/21 540 600 170 43 93/10/13 1350 1645 120 43 93/11/11 950 700 80 43 93/12/12 930 430 300 43 94/01/01 789 . 150.1 43 94/02/01 910 . 148.2 43 94/03/01 700 . 144.4 43 94/04/01 1020 . 114 44 86/11/22 6.71 203 . 118.22 44 86/11/22 7.69 . 44 86/11/22 7.93 . 17 14 44 87/04/10 6.7 320 140 150 44 87/05/29 7.55. 419.2 170 285 44 87/07/09 6.95 352 130 190 44 87/10/15 6.7 416 140 230 44 87/11/20 6.55 243.2 110 150 44 89/07/12 7.24 275.2 80 . 44 89/08/22 7.41 . 185 . 44 89/09/21 7.54 . 44 89/10/11 6.73 . 44 89/12/11 6.14 . 44 90/03/07 8.2 . 6 . 44 90/06/14 7.54 238 . 127.3 44 90/07/20 7.3 . 100.7 44 90/08/22 6.69 . 172.26 44 90/09/18 7.63 . 110 44 90/10/09 7.66 154 . 104 44 92/01/14 6.4 160 110 270 44 92/02/19 6.8 180 190 290 44 92/04/13 6.8 169 420 280 44 92/05/14 6 170 180 220 Appendix Table 2-3'a. Water quality data from the Department of Public Works and Highways (cont.p. 8) 221 Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mg CaC03/l) (mg CaC03/l) 44 93/03/18 129 150 130 44 93/08/26 6 115 90 190 44 93/10/20 144.5 100 250 44 93/11/16 117.3 160 210 44 93/12/15 108.3 130 TOO 44 94/01/01 78 . 60 44 94/02/01 130 . 121.6 44 94/03/01 124 . 150.1 44 94/04/01 120 . 136.8 45 86/11/27 7:8 311.5 . 220.4 . 45 86/11/27 6.64 45 86/11/27 6 11.5 ' 18 45 87/02/11 7.81 448 190 150 45 87/04/26 7.79 544 230 250 45 87/05/22 7.34 412 210 140 45 87/07/25 7.31 320 140 130 45 87/09/19 6.06 • 240 125 120 45 87/10/31 6.49 288 110 100 45 89/07/14 7.78 275.2 120 , 45 89/08/25 7.13 140 . 45 89/10/14 8.07 45 89/11/22 7.93 45 89/12/13 7.92 45 90/03/09 7.51 18 . 45 90/07/07 7.9 231 . 15.7.7 45 90/07/11 7,67 192 . 127.3 45 90/08/10 7.48 81.78 45 90/09/20 7.64 182, . 120 45 90/10/16 7.64 115 . 100 45 91/01/24 6.8 200 170 160 45 91/11/07 6.4 97.3 120 220 45 93/04/22 206 116 300 45 93/07/24 180 210 210 45 93/08/27 .6 119 180 130 45 93/10/28 135.9 290 40 • 45 94/01/01 164.5 . / 127.3 45 94/02/01 150 . 165.3 45 94/03/01 210 v. 218.5 45 94/04/01 200 . 193.8 48 86/11/29 7t37 14.5 21 48 87/02/11 512 215 235 48 87/04/20 448 192 172 48 87/07/25 7.57 176 155 152 48 87/12/31 6.64 416 160 190 48 89/07/14 7.6 307.2 160 . 48 89/08/25 7.94 120 : 52 86/10/16 5.4 288 90 70 Appendix Table 2-3a. Water quality data from the Department of Public Works and Highways ( cont.p. 9) Station Date Taken pH TDS Total hardness Total alkalinity Number (pH units) (ppm) (mgCaC03/l) (mg CaC03/l) 52 86/11/21 6.7 8 • • , 27 52 87/02/17 7.62 256 115 80 52 87/07/11 7.45 256 125 75 52 87/09/11 6.05 217.6 120 110 52 87/11/21 5.44 160 50 70 52 89/07/11 7.74 272 . 120 . 52 89/08/23 6.86 70 . . 52 89/10/12 7.64 52 89/11/21 7.27 52 89/12/12 7.08 52 90/07/12 7.45 126 . 91.2 52 90/08/14 6.44 74.82 52 90/09/21 7.57 178.5 . 90 52 90/10/12 7.61 185.5 . 92 57 86/11/22 6.9 57 86/11/22 6.91 254.1 . 88.08 57 86/11/22 6.82 14.5 15 57 87/04/29 384 170 160 57 87/07/27 7.86 192 130 1100 57 87/09/10 6.9 224 130 110 57 87/10/15 6.62 20 90 160 57 89/07/12 7.41 320 80 . 57 89/08/22 7.43 160 . 57 89/10/11 7.46 57 89/11/20 7.09 . ' . 57 89/12/08 6.84 57 90/03/07 7.73 32 . 57 90/06/25 6.92 160 . 71.68 57 90/07/20. 7.24 . 114 57 90/08/22 7.1 158.34 57 90/09/18 6.45 164!5 . 108 57 90/10/09 7.76 196 , 124 • ' 57 93/06/18 140 150 130 57 93/10/20 146.1 215 270 57 93/11/10 134.9 115 170 Appendix 2-4a. Sample cover letter and questionnaire used in the study 223 COVER LETTER: April 4, 1994 Dear Barangay Captain The letter that you have received contains questions regarding the protection and use of natural resources, particularly land and water in your barangay. You are one of those chosen Barangay Captains in Central Luzon to help by answering the following questions. Your answers will be used in formulating recommendations in the planning and management of our natural resources. You are assured of the confidentiality of your answers. After completing the form, please fold the questionnaire and keep it inside the accompanying stamped envelope and send it as soon as possible. It would be of much help i f you can send it before the end of May 1994. Thank you very much for your help and more power to you. Respectfully yours, MARIANO C. MAPILI, JR. Researcher 224 QUESTIONNAIRE: 1. Name 2. Age (years) 3. Occupation 4. Educational Attainment 5. How long have you resided in your present residence? years 6. The following questions concerns that portion of the river or creek that is nearest your barangay. a. What is the name of the river/creek? b. How familiar are you to the river/creek? Check one. [] Very familiar [] Somewhat familiar [] I just know its there [] I didn't even know it was there c. How attractive do you think the river/creek is? [] Very attractive [] Somewhat attractive [] Neither attractive nor unattractive fj Somewhat unattractive [] Very unattractive [] No opinion d. Are you usually aware of it when you drive by? Yes _ No e. Is the stream and its surrounding area a good place for: [] Fishing [] Wading [] Picnicking [] Sitting [] Playing []Walking [] Others (Please specify) f. Do you actually do any of these activities there? [] Fishing [] Wading []Picnicking [] Sitting [] Playing [JWalking [] Others (Please specify) g. If none of the categories above are checked, do you visit the stream at all? Yes No Why? h. Approximately how far from the stream is your house located? Check one [] 0 to 1 km [] 2 to 3 km [] 4 to 5 km [] 6 to 10 km [] more than 10 km i. How is it situated with respect to the stream? [] It is right next to the stream [] It has a view of the stream [] It lies within a five minute walk from the stream [] It is farther than five minute walk from the stream j . Would you rather live nearer to the stream or farther away from it? (In a house like your present one, disregarding inconveniences due to moving, etc.) Check one [] I would rather stay where I am now, the house is very nicely located with respect to the stream [] I would rather live in a house right next to the stream [] I would rather live in a house with a view of the stream [] I would rather live with in a five minute walk form the stream [] I would rather live even farther away: the farther the better k. Do you have other comments with regard to the effect of the stream on your decision to live near of far from it? q. Judging from your observation, how polluted do you think the stream is? [] Very polluted [] Somewhat polluted [] A little polluted [] Not at all polluted [] Don't know r. If polluted, what are the most noticeable signs of pollution in this particular stream? s. What do you think are the sources of pollution? t. How long do you think has this pollution been taking place? years u. Have there been any action in the past with regard to this source of pollution? 226 [] No action at a l l _ [] Citizen action (rallies, pickets) [] Formal complaint to the barangay captain [] File legal actions/Court cases [] Action from the provincial/ national government v. How often do you receive complaints regarding the pollution of the stream from your constituents? [] Very often [] Often [] Occasionally [] Seldom [] Never w. At what times of the year do you usually receive these complaints? Jan Feb Mar Apr May June July Aug S e p t _ Oct Nov Dec x. What are the usual forms of complaints? [] Color of water [] Smell of the water [] Garbage in the water [] Other (Please specify) y. If you had information that the stream was polluted and could identify the major polluters, what would you do? z. If your constituents had any information that the stream was polluted and could identify the major polluters, what do you think they would do? [] They would not do anything, since they would think that adequate action are being done by appropriate agencies [] Report to the barangay captain immediately [] Organize their neighbors for legal action [] Write letters to polluters [] Organize or take part in clean-ups aa. Would your constituents be willing to pay an increase in their real estate taxes to help clean up the stream? [] yes [] no Why? bb. How would you rate yourself with respect to environmental problems and pollution? [] Very concerned [] Somewhat concerned 227 [] [] [] A little concerned Not at all concerned don't know cc. Please rank the following causes of pollution: [] farming [] industries [] deforestation [] animal raising [] others (please specify) 8. The following questions are concerned with the environmental management in your barangay: a. Have you been informed of the provision in the Local Government Code that gives you power to protect the environment against pollution? b. How wereyou informed? [] through the A B C President [] through the Mayor's office [] through the Governor's office [] through the environment agencies (DENR/CENRO/PENRO) [] others (Please specify) c. If you were never informed, what might have been the reason? d. Have you been able to censure polluters employing this provision? [] not yet []yes When: Month year How f. Has the provision in the code given you additional power to enforce environmental standards in your barangay? [] yes [] no Why? g. In your opinion, is the office of the Barangay Captain the best office/agency of the government to enforce standards and catch polluters? [] yes [] no []yes rjno 228 h. Please rank the major environmental problems in your barangay: (Points from 5 to 1 with 5 points for the most pressing problem and 1 point for the least pressing problem): land conversion groundwater pollution air pollution pollution of the rivers and creeks deforestation i. Please rank the major problems in your barangay: (Points from 5 to 1 with 5 points for the most pressing problem and 1 point for the least pressing problem): peace and order situation environmental problems (pollution of air, water, land) economy/employment health housing/shelter j. What is the population of your barangay? k. Were you ever informed of the Government project called BAWASA? []YES []NO 1. How familiar are you with your barangay boundary? Please check one of the following: [] very familiar [] familiar [] fairly familiar [] not familiar [] don't know ni. What is the total land area of your barangay? has i •3 SI E 1 o * "3 £1 3 £> "£ c o 0 1 E 3 o i I cs H X '•5 1 8.3 0. co Tf i> no m © m On h O ft H >fl (*1 ^| •• » 6 » « pi » --H IS IN n » M in vo f» NO ON 00 O !>CS.-i©CSt>00l>00pHp--NOCSTfTfTf©tNpHtNinTfeN<NNO i n N i f t f l C n c ^ N C i i o q o o o o H i s i i j i o o M ^ M n o i f i i r i a o i^-««NV5h5iM^iNpid^oiiHi*inH^^ridd m m Tf — in ao 3 § ON NO IN On in r- On —1 pH _h PH r- VO Tf Tf On l> in in IS _H V) 00 CS O in r- m pH ON •n Tf in tn tn 0 0 00 NO On Tf On 0 IS On 00 IS f- tn no m 00 no IN ao m no 00 m r- 0 NO no tn On 00 00 m NO TI- On On m IN IN ig —, IN 0 m ~* IS m IS m vo 0 IS IS IS NO r- On IS m m t-IS 22 5 m 00 j^- ft © o r> ~ 1/3 90 00 ~h N N « <n J 1 0 £ £ 8 -V> O 00 VO (S 01 d ^  •--<VfiO0\©0\<SV0>rir^^<rt<rit*"0NVi00O»r»V0 © »«5 ©'©*•** se vo vd ci ^ ^ c f 00 ft N O ^ ON PH Tf 00 O IS NO 00 g NO Tf IS NO tn 0 IS IS ON m t- NO r- in l> , , tn m 00 m in On 0 00 NO n •n IS r- O On' On l> *n tn Tf in 00 in m 00 00 NO NO m m IN 00 On Tf IS 0 Tf in no r- 0 00 Tf O Tf r- NO NO Tf O 0 00 ifi — 0 m m 00 Tf m r-© IS r-IS f-00 m m On <n NO t-IS PHPH in Tf Tf l> in NO m m vo NO t- IN Tf IN IS m in PH IN vo IS m pH If) IN NO NO in m Tf O On 00 in Tf r» If) On If) On On 0 •3 0 Tf 0 in ON NO On On Tf On Tf in m On m r- e NO m Tf —* ON —h 00 tn r~ NO On O IN r- in tn in in h^ •n tn O IS O IS NO O tn Tf tn 0 ON 00 r-5? ph O Tf PH IS ph d T>' cs NO iS tn is IS IS m° d iS ph tn tn Tf fS h^ ,—1 tn d d d IS IN 4^ vd IS IN <n tn Tf IS IS 00 90 -H ON CS ft <N X —< V] vi vo vfi <no«r><rioooopmo'^ _ .. o s o o ^ r i v T v v o t R v i ^ v c r o K © © ^ " © . . . . . . . . . . h 00 o *«toocsoooo©mvooo —-- vs *-< n cn . ifi m c, in c\ 'I*1* 00 ft(SO000\N-O n v o v o - H V O N t r i M cs — ««n ~+ en 00 O N t ^ 2 - - I/) >T) "A 00^v000lSt^300^Ov^ff\00t^V0V)r000rnv0^Ow^Tj-v%rtOOM ^ r ^csrsNooooosr r ro ^ t ^ ^ o o — . 0 cs 00 2-2 O O d o o ^ m i f l o o w H ^ s hOOvCT}-|f ( (s^tv- , io O N O c s n i / jvocvor^f^o " " M ^ O N n O t - O N O f 00 ft - ' ' h N M f t m v o f t t ^ r*-t^<so\ ? ^ f t r ^ v o « s t ^ ^ - < t o o o o f f ) f t f t r ^ f t T r f t v n r - o i r t O f t v 0 ^ o e v D H V O r * O l f l O f t H V O O O i r i N O h ^ n o o r H f N f n - - ' N o n r ^ a v r i ' - i r ^ - - r i n m r- rs w rs cs o — -^ f — *h »— in «o e —< ft r- ft ft rs ft V8 in ft ft v> n cs m JS 2 *^  3 t ^ * H w o \ o o ^ H T t r ^ , « i " r ^ f t c s M ^ T r o O v o ^ v o c S v O f S v o v o f S f O ^ t ^ T CS CS 90 ^•O<S^mv - i f tO00»/3 ^d f *Sdddcs r l f svdoe 00 1^ ft ts h m n 00 \c m «o cs ft M M - ifi «n 5 00 Tf m tn Tf _< NO tn r~ 00 t- NO 0 0 Tf in 0 —« 0 m 00 On Tf O » 00 00 r> t- 0 .H O ON Tf On 0 IS tn m r- •n tn X On Tf tn ON IS Tf IS if) IS Tf NO O Tf 0 00 IS VO r- in CS NO 00 NO *H in IS 00 NO in On IS ao Tf ON 90 NO r~  IS zn 0 m 0- 00 On 00 in tn NO 00 90 PH IN Tf IS On IS m tn —1 o —1 t~ in — Tf — NO CS 00 00 »"• »n m cn cs* ri d vd TfTfONOOOOOOTfmO IN tn On r- ON On no 95 m r> m no no — 00 wi 00 ph On On PH IS NO NO 05 " M n « * 8 IS IN IN CS On IN t- NO X O h IA go N IS O cs in d m' 90 d 90 —1 ON O inNomr>i>oini>cspH ONOtnmr--TfTfONOpH CSO—"NOt^ OPHONTfNO ONTfooooooNor-mcs© no Tf in ao © PH PH IN © © p" ON Tf ph r> on tt r» © on is © in no Tf Tf CS in 90 ON Tf vi © tn ph tn 00 PH l> © PH' t^pHTfi>iNpH©ON©in©inpHt^ON©©ftinoNi^mr>pHO>Tj-tNpHXoocs tnininvoiNpHiniNr^tniNT^intni^©NoinNoi>-i>-TfcsoONpHONNONONONO o r -NOpHce in tn tnNOONm - H T f O N O i n i n i n i n - H O O t N N o o o o o T f o x N O N o ^ ONinocsNoinmt^oo -HtNoooooTfONi -ocs© » n u i o o n x f t c i C PH^TJ-TfNOpHtNCSCS TfmvtPHpHpHpH cs —* fS no m pH n in in in - H P H i n m no no vo IS IS Tf NO» 90 O PH IS PH O PH © in •n vo NO r- tn 00 0 ON no no in 00 IS pH t- On IS _ VO 00 0 if) 00 00 pH © 00 tn On CS ON On tn ON tn «n Tf NO r- IS PH NO tn 00 r- O Tf IS ON H © 0 00 PH 0 On ae 0 © © PH pH tn PH NO vd PH PH tn in m' © NO CS in H^ IS IN ^ © <N © _H © _H _H Tf i~ © tn tn Tf cs cs 30 ae — ON 0 PH cs © cs 00 00 NO m in r- O 0 0 in NO NO 00 •n m 00 00 v? 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